DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement(s)
The Information disclosure statement (IDS) filed on March 18th, 2025 has been acknowledged and considered by the examiner.
Claim Rejections - 35 USC § 101
Claims 1-20 are rejected under 101:
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim 8 along with its dependent claims 9-14 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Claim 8 is drawn to one or more computer storage media having computer-executable instructions embodied thereon that, when executed by one or more processors, cause the one or more processors to perform operations as defined in the Applicants’ disclosure’s Par. [0098], “computer storage media include volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information, such as computer-readable instructions, data structures, program modules or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by computing device 1000. Computer storage media excludes signals per se,” thus explicitly defined to encompass both transitory and non-transitory, can be a signal or carrier wave etc. since Applicants’ disclosure mentions “computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology”, Although, further in that same paragraph, Par. [0098], Applicants state “computer storage media excludes signals per se” thus reflecting contradicting disclosure in the first few sentences in the same paragraph, therefore, fail(s) to fall within at least one of the four categories of patent eligible subject matter. As these examples illustrate, the memory includes the storage media 1012.
Therefore claims 8-14 do not fit within the recognized categories of statutory subject matter. See MPEP 2106.
The office respectfully recommend the applicant to amend claim 8 and its dependent claims 9-14, limitation “One or more computer storage media having computer-executable instructions embodied thereon that, when executed by one or more processors, cause the one or more processors to perform operations” to reflect the limitation “One or more non-transitory computer storage media having computer-executable instructions embodied thereon that, when executed by one or more processors, cause the one or more processors to perform operations”.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more nor an integration of the judicial exceptions into a practical application. The limitations, under their broadest reasonable interpretation, cover mental process (concept performed in a human mind, including as observation, evaluation, judgment, opinion). The claimed invention simply perform image segmentation and image searching based on certain condition and ranking of search results. See analysis below for more details.
Regarding Independent Claim 1 and its dependent claims 2-7,
Step 1 Analysis: Claim 1 is directed to a method/process, which falls within one of the four statutory categories (process, machine, manufacture or composition of matter). Please see MPEP §2106.04.
Step 2A Prong 1 Analysis: Claim 1 recites, in part:
“segmenting the image to identify image segments, each image segment comprising an object within the image;
performing a database search for each of a first image segment and a second image segment of the identified image segments, wherein a first search result is identified for a first object of the first image segment and a second search result is identified for a second object of the second image segment based on the database search”.
The limitations as drafted, are processes that, under broadest reasonable interpretation, covers the performance of the limitation in the mind which falls within the “Mental Processes” grouping of abstract ideas. Please see MPEP §2106.04. The limitations of:
“segmenting the image to identify image segments, each image segment comprising an object within the image” is a step a human mind can perform, under BRI, using pen and paper through a process of observation and evaluation such as, the human mind can observe some data/information (images, video, already given or resulted outcome/output of data/information, etc.) and evaluate them to make a determination/identification such as observing an image and segment the image into region based on some observable condition.
“performing a database search for each of a first image segment and a second image segment of the identified image segments, wherein a first search result is identified for a first object of the first image segment and a second search result is identified for a second object of the second image segment based on the database search” is a step a human mind can perform, under BRI, using pen and paper through a process of observation and evaluation such as, the human mind can observe some data/information (images, video, already given or resulted outcome/output of data/information, etc.) and evaluate them to make a determination/identification such as performing a search by observing a database according to some observable condition of images such as their segmented regions and identify search results according to some observable data/information and conditions.
Notes: under MPEP 2106.04(a)(2)(III), mental process (thinking) “can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011): "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all." (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 [1972]). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 ("mental processes and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work’" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675).
The courts do not distinguish between mental processes that are performed entirely in the human mind and mental processes that require a human to use a physical aid (e.g., pen and paper or a slide rule) to perform the claim limitation. See, e.g., Benson, 409 U.S. at 67, 65, 175 USPQ at 674-75, 674; Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1139, 120 USPQ2d 1473, 1474 (Fed. Cir. 2016).
Nor do the courts distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer, generic circuit or device, or the likes. See " Versata Dev. Group v. SAP Am., Inc., 793 F.3d 1306, 1335, 115 USPQ2d 1681, 1702 (Fed. Cir. 2015). See also Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307, 1318, 120 USPQ2d 1353, 1360 (Fed. Cir. 2016) (‘with the exception of generic computer-implemented steps, there is nothing in the claims themselves that foreclose them from being performed by a human, mentally or with pen and paper.’’).
Because both product/device and process claims may recite a "mental process", the phrase "mental processes" should be understood as referring to the type of abstract idea, and not to the statutory category of the claim. The courts have identified numerous product claims as reciting mental process-type abstract ideas, for instance the product claims to computer systems and computer-readable media in Versata Dev. Group. v. SAP Am., Inc., 793 F.3d 1306, 115 USPQ2d 1681 (Fed. Cir. 2015).
Accordingly, the claim recites an abstract idea.
Step 2A Prong 2 Analysis: This judicial exception is not integrated into a practical application. particular, the claim recites the following additional element(s) –
one or more processors;
accessing an image;
and generating a first search results page (SRP) having both the first search result and the second search result.
The additional elements one or more processors - recited at a high level of generality (i.e. as a processor performing executing instructions stored, a memory storing instruction program, a computer to have computer components executing the instructions of the invention, a non-transitory computer readable medium performing storing instructions, generic devices [interface, screen, camera, sensor, etc.] performing well-known generic functions, etc.).
The additional elements include steps of insignificant extra-solution/post-solution activities of data gathering, data generating, data transmitting, etc. [acquiring data/information, transmitting data/info., outputting data/information, displaying data/info., converting data/info., generating data/info., etc.] such as, generating search results.
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim as a whole is directed to an abstract idea. Please see MPEP §2106.04.(d).III.C.
Step 2B Analysis: there are no additional elements, such as for these additional elements as indicated above, that amount to significantly more than the judicial exception. Please see MPEP §2106.05. The claim is directed to an abstract idea. Please see MPEP §2106.05
For all of the foregoing reasons, claim 1 does not comply with the requirements of 35 USC 101.
Accordingly, the dependent claims 2-7 do not provide elements that overcome the deficiencies of the independent claim 1.
Moreover, claim 2 recites, in part,
“providing at least a portion of the identified image segments for display at a computing device; and
receiving a selection of image segments from the portion of identified image segments provided for display, the selection comprising the first image segment and the second image segment, wherein the database search is performed for each image segment of the selection”
“providing at least a portion of the identified image segments for display at a computing device; and receiving a selection of image segments from the portion of identified image segments provided for display” are steps of insignificant extra-solution activity additional elements of data gathering such as, providing data/information for displaying, receiving data/information here being a selection.
“the selection comprising the first image segment and the second image segment, wherein the database search is performed for each image segment of the selection” provides unlimiting further specification that provide well-known generality, high level of generality further specification limitation to the limitation each depends on.
Moreover, claim 3 recites, in part,
“wherein identifying image segments is based on the object in the image segment using an object recognition model.”
wherein clause that merely provides unlimiting further specification that provide well-known generality, high level of generality further specification limitation to the limitation each depends on.
Moreover, claim 4 recites, in part,
“wherein the database search is a separate reverse image search for each of the first image segment having the first object and the second image segment having the second object.”
wherein clause that merely provides unlimiting further specification that provide well-known generality, high level of generality further specification limitation to the limitation each depends on, such as the database search is a separate reverse image search…
Moreover, claim 5 recites, in part,
“wherein the first image segment comprises the second image segment.”
wherein clause that merely provides unlimiting further specification that provide well-known generality, high level of generality further specification limitation to the limitation each depends on.
Moreover, claim 6 recites, in part,
“identifying a plurality of search results for each of the first object and the second object, wherein the first search result is identified based on the first search result being a top ranked search result among the plurality of search results for the first object, and wherein the second search result is identified based on the second search result being a top ranked search result among the plurality of search results for the second object.”
Which is a mental process activity abstract idea of observation and evaluation, judgement, merely performing identifying search results according to some observable data/information according to some observable condition
“wherein the first search result is identified based on the first search result being a top ranked search result among the plurality of search results for the first object, and wherein the second search result is identified based on the second search result being a top ranked search result among the plurality of search results for the second object” being wherein clause that merely provides unlimiting further specification that provide well-known generality, high level of generality further specification limitation to the limitation each depends on.
Moreover, claim 7 recites, in part,
“performing a second database search for each of the first image segment and the second image segment, wherein a second ranked search result is identified among the plurality of search results for the first object and a second ranked search result is identified among the plurality of search results for the second object based on the second database search; and
providing, at the first SRP, a hyperlink to a second SRP, the second SRP having both the second ranked search result for the first object and the second ranked search result for the second object.”
include steps a human mind can perform, under BRI, using pen and paper through a process of observation and evaluation such as, the human mind can observe some data/information (images, video, already given or resulted outcome/output of data/information, etc.) and evaluate them to make a determination/identification such as performing a search by observing a database according to some observable condition of images such as their segmented regions and identify search results according to some observable data/information and conditions, and ranking of such results based on observable data/information and condition.
The providing step being an insignificant extra-solution activity additional element of data gathering.
Accordingly, the dependent claims 1-7 are not patent eligible under 101.
Regarding claim 8 and its dependent claims 9-14:
The independent claim 8 recites analogous limitations to the independent claim 1, hence, is analyzed under the same approach as stated above to include limitations that are not 101 ineligible. Moreover claim 8 further recites additional elements of computer storage media having computer-executable instructions embodied thereon that, when executed by one or more processors, cause the one or more processors to perform operations, being generic computer and computer components recited at high level of generality to perform generic well-known functions.
Dependent claims 9-14 recites analogous limitations to the dependent claims 2-7, hence, analyzed under the same approach to be 101 ineligible.
Regarding claim 15 and its dependent claims 16-20:
The independent claim 15 recites analogous limitations to the independent claim 1, hence, is analyzed under the same approach as stated above to include limitations that are not 101 ineligible. Moreover claim 15 further recites additional elements of computer storage media having a system comprising: at least one processor; and one or more computer storage media storing computer readable instructions thereon that when executed by the at least one processor cause the at least one processor to perform operations, being generic computer and computer components recited at high level of generality to perform generic well-known functions.
Dependent claims 16-20 recites analogous limitations to the dependent claims 2-7, hence, analyzed under the same approach to be 101 ineligible.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 8, 10-13 and 15 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Hsin Chia Fu et. al. (“US 8,055,103 B2” hereinafter as “Fu”).
Regarding claim 8, Fu explicitly teaches one or more computer storage media having computer-executable instructions embodied thereon that, when executed by one or more processors, cause the one or more processors to perform operations comprising (Col. 2, lines 51-59, discloses “the present invention also proposes an image search system…comprises a processor, a memory and a storage device…the processor operates the image search engine”): accessing a plurality of image segments (Col. 5, lines 49-64, discloses “a user utilizes an image query interface…to input his search queries…presents several sample images…the sample images may also be the pictures uploaded by the user himself”; Col. 9, lines 20-36, discloses “the present invention proposed an object-based image search system…a user may directly specify the desired objects without using any image-segmenting software tool”; Col. 5, lines 65-67 to Col. 6, lines 1-6, disclose “the user may visually specify the interested target feature points on the sample images…to selects appropriate regions…as target feature points” these selected regions are analogous to the recited image segments), each image segment comprising a different object extracted from a single image (Col. 5, lines 65-67 to Col. 6, lines 1-6, disclose “the user may visually specify the interested target feature points on the sample images…to selects appropriate regions…as target feature points” these selected regions are analogous to the recited image segments corresponding to different objects within the image); performing a separate database search for each image segment to identify a search result for each image segment (Col 6, lines 9-18, discloses “the image search system searches for the target objects corresponding to the target feature points” indicating a plurality of objects being searched, any of which is analogous to the recited first image segment and any of the others is analogous to the recited second image segment; Col. 7, lines 22-30, discloses “compare each of the q target objects with the corresponding q candidate objects” indicating the search is performed on each of the image segments to identify a search result; Col. 7, lines 44-50, discloses “when the images of the image database contain keywords, a key-word search may be undertaken beforehand…in the image database” indicating the image results contain images obtained from a database), and generating a first search results page (SRP) having a set of combined search results that includes at least one search result for each image segment (Col. 7, lines 62-67 to Col. 8, lines 1-13, disclose “if the user wants to view the next batch of images…the image search system to transmit the next ten relevant images” indicating search results including a plurality of image results each corresponding the first object of the first image segment and the second object of the second image segment, therefore, the image result for the second object is analogous to the recited second search result; Col. 7, lines 44-50, discloses “when the images of the image database contain keywords, a key-word search may be undertaken beforehand…in the image database” indicating the image results contain images obtained from a database; FIG. 8 illustrates the search result pages including the first search result and the second search result, any of these pages is analogous to the recited first search results as claimed).
Regarding claim 10, Fu explicitly teaches the one or more computer storage media of claim 8, further comprising identifying each image segment based on the object in the image segment using an object recognition model. (Col. 6, lines 1-6, discloses “select appropriate regions on the hamburger images as target feature points…describe the above statement with a mathematical expression” therefore, the mathematical expression is analogous to the recited object recognition model since, the expression is used to recognize object in the image, note that the claim doesn’t specify what the model is therefore, the examiner construes the claimed limitation to be an expression that performs some type of object recognition task).
Regarding claim 11, Fu explicitly teaches the one or more computer storage media of claim 8, further comprising: providing each image segment for display at a computing device (Col. 4, lines 26-48, discloses “FIG. 3…showing that a hamburger image is processed into pieces of objects by the object-processing program”; moreover, Col. 6, lines 19-21, discloses “the target objects corresponding to the feature points are displayed” indicating the identified image segments as being displayed); and receiving a selection of image segments provided for display (moreover, Col. 6, lines 19-21, discloses “the target objects corresponding to the feature points are displayed” indicating the identified image segments as being displayed, indicating there is a providing and receiving of the system of such image and segments for displaying), the selection comprising a first image segment and a second image segment (Col 6, lines 9-18, discloses “the image search system searches for the target objects corresponding to the target feature points” indicating a plurality of objects being searched, any of which is analogous to the recited first image segment and any of the others is analogous to the recited second image segment; Col. 5, lines 65-67 to Col. 6, lines 1-6, disclose “the user may visually specify the interested target feature points on the sample images…to selects appropriate regions…as target feature points”), wherein the separate database search is performed for each of the first image segment and the second image segment (Col. 6, lines 29-36, discloses “the feature-similarity calculation program undertakes the similarity calculations between the target objects that the user selects and other images of the images database…the similarity between each target object and the object of the candidate image” indicating the search is performed for each object of the user’s selection).
Regarding claim 12, Fu explicitly teaches the one or more computer storage media of claim 11, wherein the first image segment comprises the second image segment (Col. 4, lines 39-54, discloses “each region may also comprises a plurality of objects. For example, a big ellipse may be firstly placed inside a similar-color region, and then several smaller ellipses are filled into the region outside the big ellipse but inside the similar-color region” therefore, to construct an object region, it can be understood to include a process of obtaining many regions and some region include the others, therefore, in this instance, the region being included is analogous to the recited second image segment, and the region including is analogous to the recited first image segment).
Regarding claim 13, Fu explicitly teaches the one or more computer storage media of claim 11, further comprising identifying the set of combined search results that includes the at least one search result for each image segment (FIG. 8 illustrates the search result pages including the first search result and the second search result, any of these pages is analogous to the recited first search results as claimed; Col. 7, lines 62-67 to Col. 8, lines 1-13, disclose “if the user wants to view the next batch of images…the image search system to transmit the next ten relevant images” indicating search results including a plurality of image results each corresponding the first object of the first image segment and the second object of the second image segment, therefore, the image result for the second object is analogous to the recited second search result; Col. 7, lines 44-50, discloses “when the images of the image database contain keywords, a key-word search may be undertaken beforehand…in the image database” indicating the image results contain images obtained from a database), wherein a first search result is identified based on the first search result being a top ranked result among a plurality of search results for the first image segment (Col. 7, lines 62-67, discloses “the top ten similar images may be presented firstly”; moreover, Col. 7, lines 22-30, discloses “comparing the similarity between the q target objects and a plurality of objects of each candidate image is to compare each of the q target objects with the corresponding q candidate objects corresponding to the target object” therefore, the similar images here being the search result corresponding to a particular object of the plurality of target objects, hence, any of which is analogous to the first object as claimed, and its search result is analogous to the first search result as claimed, the top 10 images being the a top ranked search result as claimed among the plurality of search results obtained), wherein a second search result is identified based on the second search result being a top ranked search result among a plurality of search results for the second image segment (Col. 7, lines 62-67, discloses “the top ten similar images may be presented firstly”; moreover, Col. 7, lines 22-30, discloses “comparing the similarity between the q target objects and a plurality of objects of each candidate image is to compare each of the q target objects with the corresponding q candidate objects corresponding to the target object” therefore, the similar images here being the search result corresponding to a particular object of the plurality of target objects, hence, any of the which is analogous to the first object as claimed and any of the others is analogous to the recited second object, and its search result is analogous to the second search result as claimed, the top 10 images being the a top ranked search result as claimed among the plurality of search results obtained), and wherein the set of combined search results includes the first search result and the second search result (FIG. 8 illustrates the search result pages including the first search result and the second search result, any of these pages is analogous to the recited first search results as claimed).
Regarding claim 15, Fu explicitly teaches a system comprising: at least one processor; and one or more computer storage media storing computer readable instructions thereon that when executed by the at least one processor cause the at least one processor to perform operations comprising (Col. 2, lines 51-59, discloses “the present invention also proposes an image search system…comprises a processor, a memory and a storage device…the processor operates the image search engine”): providing an image (Col. 5, lines 49-64, discloses “a user utilizes an image query interface…to input his search queries…presents several sample images…the sample images may also be the pictures uploaded by the user himself”); receiving a plurality of image segments (Col. 5, lines 49-64, discloses “a user utilizes an image query interface…to input his search queries…presents several sample images…the sample images may also be the pictures uploaded by the user himself”; Col. 9, lines 20-36, discloses “the present invention proposed an object-based image search system…a user may directly specify the desired objects without using any image-segmenting software tool”; Col. 5, lines 65-67 to Col. 6, lines 1-6, disclose “the user may visually specify the interested target feature points on the sample images…to selects appropriate regions…as target feature points” these selected regions are analogous to the recited image segments), wherein each image segment of the plurality of image segments is a portion of the image (Col. 5, lines 65-67 to Col. 6, lines 1-6, disclose “the user may visually specify the interested target feature points on the sample images…to selects appropriate regions…as target feature points” these selected regions are analogous to the recited image segments corresponding to different objects within the image) identified using an object recognition model and extracted from the image (Col. 6, lines 1-6, discloses “select appropriate regions on the hamburger images as target feature points…describe the above statement with a mathematical expression” therefore, the mathematical expression is analogous to the recited object recognition model since, the expression is used to recognize object in the image, note that the claim doesn’t specify what the model is therefore, the examiner construes the claimed limitation to be an expression that performs some type of object recognition task); providing a subset of image segments selected from the plurality of image segments (Col. 8, lines 14-23, discloses “the image search interface presents p sample images, a user selects q feature points from the p sample images” in this instance, the presented sample images is analogous to the plurality of image segments as claimed, and the user select feature points from the sample images would result in a subset of image segment as claimed); and receiving a first search results page (SRP) comprising a search result for each of the image segments in the subset (Col. 7, lines 62-67 to Col. 8, lines 1-13, disclose “if the user wants to view the next batch of images…the image search system to transmit the next ten relevant images” indicating search results including a plurality of image results each corresponding the first object of the first image segment and the second object of the second image segment, therefore, the image result for the second object is analogous to the recited second search result; Col. 7, lines 44-50, discloses “when the images of the image database contain keywords, a key-word search may be undertaken beforehand…in the image database” indicating the image results contain images obtained from a database; FIG. 8 illustrates the search result pages including the first search result and the second search result, any of these pages is analogous to the recited first search results as claimed).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-3 and 5-6 are rejected under 35 U.S.C. 103 as being unpatentable over Hsin Chia Fu et. al. (“US 8,055,103 B2” hereinafter as “Fu”) in view of Masaaki Kobayashi (“US 2014/0347513 A1” hereinafter as “Kobayashi”).
Regarding claim 1, Fu explicitly teaches a method performed by one or more processors, the method comprising (Col. 2, lines 51-59, discloses “the present invention also proposes an image search system…comprises a processor, a memory and a storage device…the processor operates the image search engine”): accessing an image (Col. 5, lines 49-64, discloses “a user utilizes an image query interface…to input his search queries…presents several sample images…the sample images may also be the pictures uploaded by the user himself”); process the image to identify image segments (Col. 9, lines 20-36, discloses “the present invention proposed an object-based image search system…a user may directly specify the desired objects without using any image-segmenting software tool”; Col. 5, lines 65-67 to Col. 6, lines 1-6, disclose “the user may visually specify the interested target feature points on the sample images…to selects appropriate regions…as target feature points” these selected regions are analogous to the recited image segments), each image segment comprising an object within the image (Col. 5, lines 65-67 to Col. 6, lines 1-6, disclose “the user may visually specify the interested target feature points on the sample images…to selects appropriate regions…as target feature points” these selected regions are analogous to the recited image segments corresponding to different objects within the image); performing a database search for each of a first image segment and a second image segment of the identified image segments (Col 6, lines 9-18, discloses “the image search system searches for the target objects corresponding to the target feature points” indicating a plurality of objects being searched, any of which is analogous to the recited first image segment and any of the others is analogous to the recited second image segment), wherein a first search result is identified for a first object of the first image segment (Col. 7, lines 62-67 to Col. 8, lines 1-13, disclose “if the user wants to view the next batch of images…the image search system to transmit the next ten relevant images” indicating search results including a plurality of image results each corresponding the first object of the first image segment and the second object of the second image segment, therefore, the image result for the first object is analogous to the recited first search result) and a second search result is identified for a second object of the second image segment based on the database search (Col. 7, lines 62-67 to Col. 8, lines 1-13, disclose “if the user wants to view the next batch of images…the image search system to transmit the next ten relevant images” indicating search results including a plurality of image results each corresponding the first object of the first image segment and the second object of the second image segment, therefore, the image result for the second object is analogous to the recited second search result; Col. 7, lines 44-50, discloses “when the images of the image database contain keywords, a key-word search may be undertaken beforehand…in the image database” indicating the image results contain images obtained from a database); and generating a first search results page (SRP) having both the first search result and the second search result (FIG. 8 illustrates the search result pages including the first search result and the second search result, any of these pages is analogous to the recited first search results as claimed).
However, Fu does not explicitly teach segmenting the image to identify image segments.
Kobayashi explicitly teaches segmenting the image to identify image segments (Par. [0034] discloses “on the screen shown…the user can switch on/off of setting of the region (priority feature point detection region) to detect a feature point by touching a segmented region” indicating the user select a segmented region on the image displayed; moreover, Par. [0038] discloses “segmented images in a fixed segmentation pattern” indicates the segmented regions obtained from a segmentation process).
Therefore, it would have been obvious to one or ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teaches of Fu of having a method performed by one or more processors, the method comprising: accessing an image; process the image to identify image segments, each image segment comprising an object within the image; performing a database search for each of a first image segment and a second image segment of the identified image segments, wherein a first search result is identified for a first object of the first image segment and a second search result is identified for a second object of the second image segment based on the database search; and generating a first search results page (SRP) having both the first search result and the second search result, with the teachings of Kobayashi of segmenting the image to identify image segments.
Wherein having Fu‘s method performed by one or more processors, the method comprising: accessing an image; segmenting the image to identify image segments, each image segment comprising an object within the image; performing a database search for each of a first image segment and a second image segment of the identified image segments, wherein a first search result is identified for a first object of the first image segment and a second search result is identified for a second object of the second image segment based on the database search; and generating a first search results page (SRP) having both the first search result and the second search result.
The motivation behind the modification would have been to perform image search more accurately based on user selection for object search without user having to perform further segmenting, and allow for feature points detection based on image segmenting thereby, reduce the load of feature point detection processing. Since both Fu and Kobayashi share the same endeavor of user selection to identify object feature. Wherein Fu’s system performs image search more accurately based on user selection for object search without user having to perform further segmenting, see Fu’s Abstract and Col. 1, lines 43-64 and Kobayashi’s allow for feature points detection based on image segmenting thereby, reduce the load of feature point detection processing, see Kobayashi’s Par. [0099].
Regarding claim 2, Fu in view of Kobayashi explicitly teaches the method of claim 1, Fu explicitly teaches further comprising: providing at least a portion of the identified image segments for display at a computing device (Col. 4, lines 26-48, discloses “FIG. 3…showing that a hamburger image is processed into pieces of objects by the object-processing program”; moreover, Col. 6, lines 19-21, discloses “the target objects corresponding to the feature points are displayed” indicating the identified image segments as being displayed); and receiving a selection of image segments from the portion of identified image segments provided for display (moreover, Col. 6, lines 19-21, discloses “the target objects corresponding to the feature points are displayed” indicating the identified image segments as being displayed, indicating there is a providing and receiving of the system of such image and segments for displaying), the selection comprising the first image segment and the second image segment (Col 6, lines 9-18, discloses “the image search system searches for the target objects corresponding to the target feature points” indicating a plurality of objects being searched, any of which is analogous to the recited first image segment and any of the others is analogous to the recited second image segment; Col. 5, lines 65-67 to Col. 6, lines 1-6, disclose “the user may visually specify the interested target feature points on the sample images…to selects appropriate regions…as target feature points”), wherein the database search is performed for each image segment of the selection (Col. 6, lines 29-36, discloses “the feature-similarity calculation program undertakes the similarity calculations between the target objects that the user selects and other images of the images database…the similarity between each target object and the object of the candidate image” indicating the search is performed for each object of the user’s selection).
Regarding claim 3, Fu in view of Kobayashi explicitly teaches the method of claim 1, wherein Fu explicitly teaches identifying image segments is based on the object in the image segment using an object recognition model (Col. 6, lines 1-6, discloses “select appropriate regions on the hamburger images as target feature points…describe the above statement with a mathematical expression” therefore, the mathematical expression is analogous to the recited object recognition model since, the expression is used to recognize object in the image, note that the claim doesn’t specify what the model is therefore, the examiner construes the claimed limitation to be an expression that performs some type of object recognition task).
Regarding claim 5, Fu in view of Kobayashi explicitly teaches the method of claim 1, wherein Fu explicitly teaches wherein the first image segment comprises the second image segment (Col. 4, lines 39-54, discloses “each region may also comprises a plurality of objects. For example, a big ellipse may be firstly placed inside a similar-color region, and then several smaller ellipses are filled into the region outside the big ellipse but inside the similar-color region” therefore, to construct an object region, it can be understood to include a process of obtaining many regions and some region include the others, therefore, in this instance, the region being included is analogous to the recited second image segment, and the region including is analogous to the recited first image segment).
Regarding claim 6, Fu in view of Kobayashi explicitly teaches the method of claim 1, wherein Fu explicitly teaches further comprising identifying a plurality of search results for each of the first object and the second object (FIG. 8 illustrates the search result pages including the first search result and the second search result, any of these pages is analogous to the recited first search results as claimed; Col. 7, lines 62-67 to Col. 8, lines 1-13, disclose “if the user wants to view the next batch of images…the image search system to transmit the next ten relevant images” indicating search results including a plurality of image results each corresponding the first object of the first image segment and the second object of the second image segment, therefore, the image result for the second object is analogous to the recited second search result; Col. 7, lines 44-50, discloses “when the images of the image database contain keywords, a key-word search may be undertaken beforehand…in the image database” indicating the image results contain images obtained from a database), wherein the first search result is identified based on the first search result being a top ranked search result among the plurality of search results for the first object (Col. 7, lines 62-67, discloses “the top ten similar images may be presented firstly”; moreover, Col. 7, lines 22-30, discloses “comparing the similarity between the q target objects and a plurality of objects of each candidate image is to compare each of the q target objects with the corresponding q candidate objects corresponding to the target object” therefore, the similar images here being the search result corresponding to a particular object of the plurality of target objects, hence, any of which is analogous to the first object as claimed, and its search result is analogous to the first search result as claimed, the top 10 images being the a top ranked search result as claimed among the plurality of search results obtained), and wherein the second search result is identified based on the second search result being a top ranked search result among the plurality of search results for the second object (Col. 7, lines 62-67, discloses “the top ten similar images may be presented firstly”; moreover, Col. 7, lines 22-30, discloses “comparing the similarity between the q target objects and a plurality of objects of each candidate image is to compare each of the q target objects with the corresponding q candidate objects corresponding to the target object” therefore, the similar images here being the search result corresponding to a particular object of the plurality of target objects, hence, any of the which is analogous to the first object as claimed and any of the others is analogous to the recited second object, and its search result is analogous to the second search result as claimed, the top 10 images being the a top ranked search result as claimed among the plurality of search results obtained).
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Hsin Chia Fu et. al. (“US 8,055,103 B2” hereinafter as “Fu”) in view of Masaaki Kobayashi (“US 2014/0347513 A1” hereinafter as “Kobayashi”) and Xin Xin et. al. (“US 2014/0195560 A1” hereinafter as “Xin”).
Regarding claim 4, Fu in view of Kobayashi explicitly teaches the method of claim 1.
However, Fu in view of Kobayashi does not explicitly teach wherein the database search is a separate reverse image search for each of the first image segment having the first object and the second image segment having the second object.
Xin explicitly teaches wherein the database search is a separate reverse image search (Par. [0034] discloses “descriptor matching functionality provides two-way matching of local features between the query image and repository images within database”; moreover, Par. [0040] discloses “two-way SIFT point matching-first “forward”, between SIFT points in the query image and those in the repository image, and then “backward”, between SIFT points in a repository image and those in the query image” indicating the database search is a separate backward search, which is analogous to the recited reverse image search) for each of the first image segment having the first object (Par. [0042] discloses “two way local feature matching to improve accuracy…for a set of n local features…and a set of m local features” indicating feature matching which is analogous to Fu’s feature matching, Fu teaches each feature correspond to an image region, hence, the plurality of features of Xin is analogous to a plurality of image regions, therefore, the search is performed for each features is analogous to for each of the first image segment having the first object as claimed) and the second image segment having the second object (Par. [0042] discloses “two way local feature matching to improve accuracy…for a set of n local features…and a set of m local features” indicating feature matching which is analogous to Fu’s feature matching, Fu teaches each feature correspond to an image region, hence, the plurality of features of Xin is analogous to a plurality of image regions, therefore, the search is performed for each features is analogous to for each of the second image segment having the second object as claimed).
Therefore, it would have been obvious to one or ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teaches of Fu in view of Kobayashi of having a method performed by one or more processors, the method comprising: accessing an image; process the image to identify image segments, with the teachings of Xin of having wherein the database search is a separate reverse image search for each of the first image segment having the first object and the second image segment having the second object.
Wherein having Fu‘s method performed by one or more processors, the method comprising: accessing an image; process the image to identify image segments, wherein the database search is a separate reverse image search for each of the first image segment having the first object and the second image segment having the second object.
The motivation behind the modification would have been to perform image search more accurately based on user selection for object search without user having to perform further segmenting, and perform image searching more accurately by perform two way search. Since both Fu and Xin share the same endeavor of image search based on image feature. Wherein Fu’s system performs image search more accurately based on user selection for object search without user having to perform further segmenting, see Fu’s Abstract and Col. 1, lines 43-64 and Xin’s allow for performing image searching more accurately by perform two way search, see Xin’s Par. [0042].
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Hsin Chia Fu et. al. (“US 8,055,103 B2” hereinafter as “Fu”) in view of Masaaki Kobayashi (“US 2014/0347513 A1” hereinafter as “Kobayashi”) and Marcus Fest (“US 2001/0047375 A1” hereinafter as “Fest”).
Regarding claim 7, Fu in view of Kobayashi explicitly teaches the method of claim 6, wherein Fu explicitly teaches further comprising: performing a second database search for each of the first image segment and the second image segment (Col. 6, lines 22-26, discloses “the user determines whether the presented target objects are exactly what he wants. If they are not, the process returns to Step S503 to select another target feature points again. The same process will be repeated until satisfactory target objects are obtained” indicating a second database search is performed for the features being each of the first and second image segments), wherein a second ranked search result is identified among the plurality of search results for the first object (Col. 7, lines 62-67, discloses “the top ten similar images may be presented firstly”; moreover, Col. 7, lines 22-30, discloses “comparing the similarity between the q target objects and a plurality of objects of each candidate image is to compare each of the q target objects with the corresponding q candidate objects corresponding to the target object” therefore, the similar images here being the search result corresponding to a particular object of the plurality of target objects, hence, any of which is analogous to the first object as claimed, and its search result is analogous to the first search result as claimed, the top 10 images being the a top ranked search result as claimed among the plurality of search results obtained; the search for the second database search results in ranked search result this instance, is analogous to the recited second ranked search result as claimed) and a second ranked search result is identified among the plurality of search results for the second object based on the second database search (Col. 7, lines 62-67, discloses “the top ten similar images may be presented firstly”; moreover, Col. 7, lines 22-30, discloses “comparing the similarity between the q target objects and a plurality of objects of each candidate image is to compare each of the q target objects with the corresponding q candidate objects corresponding to the target object” therefore, the similar images here being the search result corresponding to a particular object of the plurality of target objects, hence, any of the which is analogous to the first object as claimed and any of the others is analogous to the recited second object, and its search result is analogous to the second search result as claimed, the top 10 images being the a top ranked search result as claimed among the plurality of search results obtained; the search for the second database search results in ranked search result this instance, is analogous to the recited second ranked search result as claimed); and providing, at the first SRP, an option to a second SRP (Col. 7, lines 62-67, discloses “if the user ants to view the next batches of images, he may click on the “Next” button to ask the image search system to transmit the next ten relevant images” indicating the option to send from one view of search result to the next search result), the second SRP having both the second ranked search result for the first object and the second ranked search result for the second object (FIG. 8 illustrates the search result pages including the first search result and the second search result, any of these pages is analogous to the recited first search results as claimed, including the ranked results, the result pages of the second search is analogous to the recited second SRP as claimed).
However, Fu in view of Kobayashi does not explicitly teach the option being a hyperlink.
Fest explicitly teaches the option being a hyperlink (Par. [0005] discloses “Back button…to return to page with the original hyperlink” therefore, the back and next buttons of Fu can be understood to be returning to a hyperlink as taught by Fest).
Therefore, it would have been obvious to one or ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teaches of Fu in view of Kobayashi of having a system to have a first image search identifies a first search result for a first image segment and a second image search identifies a second search result for a second image segment, the first SRP comprising the first search result and the second search result, performing a second database search for each of the first image segment and the second image segment, wherein a second ranked search result is identified among the plurality of search results for the first object and a second ranked search result is identified among the plurality of search results for the second object based on the second database search; and providing, at the first SRP, an option to a second SRP, the second SRP having both the second ranked search result for the first object and the second ranked search result for the second object, with the teachings of Fest of having the option being a hyperlink.
Wherein having Fu‘s a system to have a first image search identifies a first search result for a first image segment and a second image search identifies a second search result for a second image segment, the first SRP comprising the first search result and the second search result, performing a second database search for each of the first image segment and the second image segment, wherein a second ranked search result is identified among the plurality of search results for the first object and a second ranked search result is identified among the plurality of search results for the second object based on the second database search; and providing, at the first SRP, an option to a second SRP, the second SRP having both the second ranked search result for the first object and the second ranked search result for the second object, the option being a hyperlink.
The motivation behind the modification would have been to perform image search more accurately based on user selection for object search without user having to perform further segmenting, and perform image searching more accurately by perform two way search and allow for more interactive user-interface navigation. Since both Fu and Fest share the same endeavor of navigating through web pages. Wherein Fu’s system performs image search more accurately based on user selection for object search without user having to perform further segmenting, see Fu’s Abstract and Col. 1, lines 43-64 and Fest’s allow for allow for more interactive user-interface navigation, see Fest’s Par. [0008].
Claims 9 and 16-19 are rejected under 35 U.S.C. 103 as being unpatentable over Hsin Chia Fu et. al. (“US 8,055,103 B2” hereinafter as “Fu”) in view of Xin Xin et. al. (“US 2014/0195560 A1” hereinafter as “Xin”).
Regarding claim 9, Fu explicitly teaches the one or more computer storage media of claim 8.
However, Fu does not explicitly teach wherein performing the separate database searches comprises performing a reverse image search for each image segment.
Xin explicitly teaches wherein performing the separate database searches (Par. [0034] discloses “descriptor matching functionality provides two-way matching of local features between the query image and repository images within database”; moreover, Par. [0040] discloses “two-way SIFT point matching-first “forward”, between SIFT points in the query image and those in the repository image, and then “backward”, between SIFT points in a repository image and those in the query image” indicating the database search is a separate backward search, which is analogous to the recited reverse image search) comprises performing a reverse image search for each image segment (Par. [0042] discloses “two way local feature matching to improve accuracy…for a set of n local features…and a set of m local features” indicating feature matching which is analogous to Fu’s feature matching, Fu teaches each feature correspond to an image region, hence, the plurality of features of Xin is analogous to a plurality of image regions, therefore, the search is performed for each features is analogous to for each of the first image segment having the first object as claimed).
Therefore, it would have been obvious to one or ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teaches of Fu of having a system performed by one or more processors, the method comprising: accessing an image; process the image to identify image segments, with the teachings of Xin of having wherein performing the separate database searches comprises performing a reverse image search for each image segment.
Wherein having Fu‘s system performed by one or more processors, the method comprising: accessing an image; process the image to identify image segments, wherein performing the separate database searches comprises performing a reverse image search for each image segment.
The motivation behind the modification would have been to perform image search more accurately based on user selection for object search without user having to perform further segmenting, and perform image searching more accurately by perform two way search. Since both Fu and Xin share the same endeavor of image search based on image feature. Wherein Fu’s system performs image search more accurately based on user selection for object search without user having to perform further segmenting, see Fu’s Abstract and Col. 1, lines 43-64 and Xin’s allow for performing image searching more accurately by perform two way search, see Xin’s Par. [0042].
Regarding claim 16, Fu explicitly teaches the system of claim 15.
However, Fu does not explicitly teach wherein the search result for each of the image segments in the subset is determined from a separate reverse image search for each of the image segments.
Xin explicitly teaches wherein the search result for each of the image segments in the subset is determined from a separate reverse image search for each of the image segments (Par. [0034] discloses “descriptor matching functionality provides two-way matching of local features between the query image and repository images within database”; moreover, Par. [0040] discloses “two-way SIFT point matching-first “forward”, between SIFT points in the query image and those in the repository image, and then “backward”, between SIFT points in a repository image and those in the query image” indicating the database search is a separate backward search, which is analogous to the recited reverse image search; Par. [0042] discloses “two way local feature matching to improve accuracy…for a set of n local features…and a set of m local features” indicating feature matching which is analogous to Fu’s feature matching, Fu teaches each feature correspond to an image region, hence, the plurality of features of Xin is analogous to a plurality of image regions, therefore, the search is performed for each features is analogous to for each of the first image segment having the first object as claimed).
Therefore, it would have been obvious to one or ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teaches of Fu of having a system performed by one or more processors, the method comprising: accessing an image; process the image to identify image segments, with the teachings of Xin of having wherein the search result for each of the image segments in the subset is determined from a separate reverse image search for each of the image segments.
Wherein having Fu‘s system performed by one or more processors, the method comprising: accessing an image; process the image to identify image segments, wherein the search result for each of the image segments in the subset is determined from a separate reverse image search for each of the image segments.
The motivation behind the modification would have been to perform image search more accurately based on user selection for object search without user having to perform further segmenting, and perform image searching more accurately by perform two way search. Since both Fu and Xin share the same endeavor of image search based on image feature. Wherein Fu’s system performs image search more accurately based on user selection for object search without user having to perform further segmenting, see Fu’s Abstract and Col. 1, lines 43-64 and Xin’s allow for performing image searching more accurately by perform two way search, see Xin’s Par. [0042].
Regarding claim 17, Fu in view of Xin explicitly teaches the system of claim 16, wherein Fu explicitly teaches a first image search identifies a first search result for a first image segment (Col 6, lines 9-18, discloses “the image search system searches for the target objects corresponding to the target feature points” indicating a plurality of objects being searched, any of which is analogous to the recited first image segment and any of the others is analogous to the recited second image segment; FIG. 8 illustrates the search result pages including the first search result and the second search result, any of these pages is analogous to the recited first search results as claimed) and a second image search identifies a second search result for a second image segment (Col. 7, lines 62-67 to Col. 8, lines 1-13, disclose “if the user wants to view the next batch of images…the image search system to transmit the next ten relevant images” indicating search results including a plurality of image results each corresponding the first object of the first image segment and the second object of the second image segment, therefore, the image result for the second object is analogous to the recited second search result; Col. 7, lines 44-50, discloses “when the images of the image database contain keywords, a key-word search may be undertaken beforehand…in the image database” indicating the image results contain images obtained from a database), the first SRP comprising the first search result and the second search result (FIG. 8 illustrates the search result pages including the first search result and the second search result, any of these pages is analogous to the recited first search results as claimed).
However, Fu does not explicitly teach the image search being a reverse image search.
Xin explicitly teaches the image search being a reverse image search (Par. [0034] discloses “descriptor matching functionality provides two-way matching of local features between the query image and repository images within database”; moreover, Par. [0040] discloses “two-way SIFT point matching-first “forward”, between SIFT points in the query image and those in the repository image, and then “backward”, between SIFT points in a repository image and those in the query image” indicating the database search is a separate backward search, which is analogous to the recited reverse image search; Par. [0042] discloses “two way local feature matching to improve accuracy…for a set of n local features…and a set of m local features” indicating feature matching which is analogous to Fu’s feature matching, Fu teaches each feature correspond to an image region, hence, the plurality of features of Xin is analogous to a plurality of image regions, therefore, the search is performed for each features is analogous to for each of the first image segment having the first object as claimed).
Therefore, it would have been obvious to one or ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teaches of Fu of having a system to have a first image search identifies a first search result for a first image segment and a second image search identifies a second search result for a second image segment, the first SRP comprising the first search result and the second search result, with the teachings of Xin of having wherein the image search being a reverse image search.
Wherein having Fu‘s system to have a first image search identifies a first search result for a first image segment and a second image search identifies a second search result for a second image segment, the first SRP comprising the first search result and the second search result, wherein the image search being a reverse image search.
The motivation behind the modification would have been to perform image search more accurately based on user selection for object search without user having to perform further segmenting, and perform image searching more accurately by perform two way search. Since both Fu and Xin share the same endeavor of image search based on image feature. Wherein Fu’s system performs image search more accurately based on user selection for object search without user having to perform further segmenting, see Fu’s Abstract and Col. 1, lines 43-64 and Xin’s allow for performing image searching more accurately by perform two way search, see Xin’s Par. [0042].
Regarding claim 18, Fu in view of Xin explicitly teaches the system of claim 17, wherein Fu explicitly teaches the first search result is a top ranked search result among a plurality of search results for the first image segment (Col. 7, lines 62-67, discloses “the top ten similar images may be presented firstly”; moreover, Col. 7, lines 22-30, discloses “comparing the similarity between the q target objects and a plurality of objects of each candidate image is to compare each of the q target objects with the corresponding q candidate objects corresponding to the target object” therefore, the similar images here being the search result corresponding to a particular object of the plurality of target objects, hence, any of which is analogous to the first object as claimed, and its search result is analogous to the first search result as claimed, the top 10 images being the a top ranked search result as claimed among the plurality of search results obtained) and the second search result is a top ranked search result among a plurality of search results for the second image segment (Col. 7, lines 62-67, discloses “the top ten similar images may be presented firstly”; moreover, Col. 7, lines 22-30, discloses “comparing the similarity between the q target objects and a plurality of objects of each candidate image is to compare each of the q target objects with the corresponding q candidate objects corresponding to the target object” therefore, the similar images here being the search result corresponding to a particular object of the plurality of target objects, hence, any of the which is analogous to the first object as claimed and any of the others is analogous to the recited second object, and its search result is analogous to the second search result as claimed, the top 10 images being the a top ranked search result as claimed among the plurality of search results obtained).
Regarding claim 19, Fu in view of Xin explicitly teaches the system of claim 18, wherein Fu explicitly teaches the first image segment comprises the second image segment (Col. 4, lines 39-54, discloses “each region may also comprises a plurality of objects. For example, a big ellipse may be firstly placed inside a similar-color region, and then several smaller ellipses are filled into the region outside the big ellipse but inside the similar-color region” therefore, to construct an object region, it can be understood to include a process of obtaining many regions and some region include the others, therefore, in this instance, the region being included is analogous to the recited second image segment, and the region including is analogous to the recited first image segment).
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Hsin Chia Fu et. al. (“US 8,055,103 B2” hereinafter as “Fu”) in view of Marcus Fest (“US 2001/0047375 A1” hereinafter as “Fest”).
Regarding claim 14, Fu explicitly teaches the one or more computer storage media of claim 12, further comprising providing, at the first SRP, an option to a second SRP (Col. 6, lines 22-26, discloses “the user determines whether the presented target objects are exactly what he wants. If they are not, the process returns to Step S503 to select another target feature points again. The same process will be repeated until satisfactory target objects are obtained” indicating a second database search is performed for the features being each of the first and second image segments; Col. 7, lines 62-67, discloses “if the user ants to view the next batches of images, he may click on the “Next” button to ask the image search system to transmit the next ten relevant images” indicating the option to send from one view of search result to the next search result), the second SRP having both a second ranked search result for the first image segment and a second ranked search result for the second image segment (FIG. 8 illustrates the search result pages including the first search result and the second search result, any of these pages is analogous to the recited first search results as claimed, including the ranked results, the result pages of the second search is analogous to the recited second SRP as claimed; Col. 7, lines 62-67, discloses “the top ten similar images may be presented firstly”; moreover, Col. 7, lines 22-30, discloses “comparing the similarity between the q target objects and a plurality of objects of each candidate image is to compare each of the q target objects with the corresponding q candidate objects corresponding to the target object” therefore, the similar images here being the search result corresponding to a particular object of the plurality of target objects, hence, any of the which is analogous to the first object as claimed and any of the others is analogous to the recited second object, and its search result is analogous to the second search result as claimed, the top 10 images being the a top ranked search result as claimed among the plurality of search results obtained; the search for the second database search results in ranked search result this instance, is analogous to the recited second ranked search result as claimed).
However, Fu does not explicitly teach the option being a hyperlink.
Fest explicitly teaches the option being a hyperlink (Par. [0005] discloses “Back button…to return to page with the original hyperlink” therefore, the back and next buttons of Fu can be understood to be returning to a hyperlink as taught by Fest).
Therefore, it would have been obvious to one or ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teaches of Fu of having a system to have a first image search identifies a first search result for a first image segment and a second image search identifies a second search result for a second image segment, the first SRP comprising the first search result and the second search result, performing a second database search for each of the first image segment and the second image segment, wherein a second ranked search result is identified among the plurality of search results for the first object and a second ranked search result is identified among the plurality of search results for the second object based on the second database search; and providing, at the first SRP, an option to a second SRP, the second SRP having both the second ranked search result for the first object and the second ranked search result for the second object, with the teachings of Fest of having the option being a hyperlink.
Wherein having Fu‘s a system to have a first image search identifies a first search result for a first image segment and a second image search identifies a second search result for a second image segment, the first SRP comprising the first search result and the second search result, performing a second database search for each of the first image segment and the second image segment, wherein a second ranked search result is identified among the plurality of search results for the first object and a second ranked search result is identified among the plurality of search results for the second object based on the second database search; and providing, at the first SRP, an option to a second SRP, the second SRP having both the second ranked search result for the first object and the second ranked search result for the second object, the option being a hyperlink.
The motivation behind the modification would have been to perform image search more accurately based on user selection for object search without user having to perform further segmenting, and perform image searching more accurately by perform two way search and allow for more interactive user-interface navigation. Since both Fu and Fest share the same endeavor of navigating through web pages. Wherein Fu’s system performs image search more accurately based on user selection for object search without user having to perform further segmenting, see Fu’s Abstract and Col. 1, lines 43-64 and Fest’s allow for allow for more interactive user-interface navigation, see Fest’s Par. [0008].
Claim 20 is rejected under 35 U.S.C. 103 as being unpatentable over Hsin Chia Fu et. al. (“US 8,055,103 B2” hereinafter as “Fu”) in view of Masaaki Kobayashi (“US 2014/0347513 A1” hereinafter as “Kobayashi”) and Marcus Fest (“US 2001/0047375 A1” hereinafter as “Fest”).
Regarding claim 20, Fu in view of Kobayashi explicitly teaches the system of claim 18, Fu explicitly teaches further comprising receiving an input at an option to a second SRP that is provided at the first SRP (Col. 6, lines 22-26, discloses “the user determines whether the presented target objects are exactly what he wants. If they are not, the process returns to Step S503 to select another target feature points again. The same process will be repeated until satisfactory target objects are obtained” indicating a second database search is performed for the features being each of the first and second image segments; Col. 7, lines 62-67, discloses “if the user ants to view the next batches of images, he may click on the “Next” button to ask the image search system to transmit the next ten relevant images” indicating the option to send from one view of search result to the next search result), the second SRP having both a second ranked search result for the first image segment and a second ranked search result for the second image segment (FIG. 8 illustrates the search result pages including the first search result and the second search result, any of these pages is analogous to the recited first search results as claimed, including the ranked results, the result pages of the second search is analogous to the recited second SRP as claimed; Col. 7, lines 62-67, discloses “the top ten similar images may be presented firstly”; moreover, Col. 7, lines 22-30, discloses “comparing the similarity between the q target objects and a plurality of objects of each candidate image is to compare each of the q target objects with the corresponding q candidate objects corresponding to the target object” therefore, the similar images here being the search result corresponding to a particular object of the plurality of target objects, hence, any of the which is analogous to the first object as claimed and any of the others is analogous to the recited second object, and its search result is analogous to the second search result as claimed, the top 10 images being the a top ranked search result as claimed among the plurality of search results obtained; the search for the second database search results in ranked search result this instance, is analogous to the recited second ranked search result as claimed).
However, Fu does not explicitly teach the option being a hyperlink.
Fest explicitly teaches the option being a hyperlink (Par. [0005] discloses “Back button…to return to page with the original hyperlink” therefore, the back and next buttons of Fu can be understood to be returning to a hyperlink as taught by Fest).
Therefore, it would have been obvious to one or ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teaches of Fu of having a system to have a first image search identifies a first search result for a first image segment and a second image search identifies a second search result for a second image segment, the first SRP comprising the first search result and the second search result, performing a second database search for each of the first image segment and the second image segment, wherein a second ranked search result is identified among the plurality of search results for the first object and a second ranked search result is identified among the plurality of search results for the second object based on the second database search; and providing, at the first SRP, an option to a second SRP, the second SRP having both the second ranked search result for the first object and the second ranked search result for the second object, with the teachings of Fest of having the option being a hyperlink.
Wherein having Fu‘s a system to have a first image search identifies a first search result for a first image segment and a second image search identifies a second search result for a second image segment, the first SRP comprising the first search result and the second search result, performing a second database search for each of the first image segment and the second image segment, wherein a second ranked search result is identified among the plurality of search results for the first object and a second ranked search result is identified among the plurality of search results for the second object based on the second database search; and providing, at the first SRP, an option to a second SRP, the second SRP having both the second ranked search result for the first object and the second ranked search result for the second object, the option being a hyperlink.
The motivation behind the modification would have been to perform image search more accurately based on user selection for object search without user having to perform further segmenting, and perform image searching more accurately by perform two way search and allow for more interactive user-interface navigation. Since both Fu and Fest share the same endeavor of navigating through web pages. Wherein Fu’s system performs image search more accurately based on user selection for object search without user having to perform further segmenting, see Fu’s Abstract and Col. 1, lines 43-64 and Fest’s allow for allow for more interactive user-interface navigation, see Fest’s Par. [0008].
Pertinent Prior Art(s)
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
KIM; Jung-Tae, “US 20150310012 A1”, discloses an object-based image search system effectively searches for a registered image or video having a configuration of object-based information similar to that of information input by a user or information related to the registered image or video. The searching system for object-based images is classifying or clustering registered images or videos according to feature points and attributes of the feature points in an object-based manner, and, if a user uploads an image or a video or searches for an image using a voice or text through a user terminal such as a PC, a tablet computer, a mobile terminal, a connected TV or the like, simply searching for matched images or videos from the registered images or the registered videos and providing the user terminal with a corresponding result or related information..
Spears; Logan, “US 20220198209 A1”, discloses an example system includes a first and second digital device. The first digital device may be configured to provide an interface displaying an image including a depiction of an object, place a bounding shape around the object, and crop contents of the bounding shape to create a portion. The second digital device may be configured to receive the portion, retrieve high-level features and low-level features, apply first Atrous Spatial Pyramid Pooling (ASPP) to the high-level features to aggregate the high-level features as aggregate features, concatenate results to create the aggregate features, up-sample, apply a convolution to the low-level features, concatenate the aggregate features with the low-level features after convolution to form combined features, segment the combined features to generate a polygonal shape outline along outer boundaries of the first object, and provide the first polygonal shape outline to the first digital device for display.
Conclusion
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/PHUONG HAU CAI/Examiner, Art Unit 2673
/CHINEYERE WILLS-BURNS/Supervisory Patent Examiner, Art Unit 2673
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