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 .
Status of Claims
This action is in response to amendment filed on 27 January 2026. Claims 1, 3, 5, 10, and 14-16 have been amended. Claims 2 and 4 have been cancelled. Claims 1, 3, and 5-16 are currently pending and have been examined.
Claim Rejections - 35 USC § 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.
Step 1: The claims 1, 3, and 5-7, 10 and 11 are a method claims 8, 9, 12 and 15 are a media and claims 13, 14, and 16 are a system/device. Thus, each independent claim, on its face, is directed to one of the statutory categories of 35 U.S.C. §101. However, the claims 1, 3 and 5-16 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 2A-Prong 1: claims recite determining at least one first key image from a first user for a target object with an advertising requirement; upon receiving an information search request initiated by a second user based on a second key image comprising a search object , determining matching search results according to the second key image, and determining whether the target object shown in each of the at least one first key image and the searched object shown in the second key image belong to a same product category, in response to determining that the target object and the searched object belong to the same product category, determining, based on the product category, whether a first attribute of the searched object is a key attribute, the first attribute comprising color, performing a similarity comparison between the second key image and the at least one first key image by performing a pixel-by-pixel comparison of a main image region of the second key image showing the searched object and a main image region of the at least one first key image showing the target object to determine a degree of match between the second key image and the at least one first key image, wherein the pixel-by-pixel comparison includes the first attribute when the first attribute is determined to be the key attribute, and ignores the first attribute or assigns a lower weight to the first attribute when the first attribute is determined not to be the key attribute; based on the degree of match, deteriming whether the target object bound to the at least one first key image qualifies to compete for a target display resource on a search result page displying the matching search results, wherein the targe disply resource is provided to meet the advertising requirement. The steps—determining if objects are in the same category, identifying key attributes (like color), and performing a weighted pixel-by-pixel comparison—are viewed as mental processes (e.g., observing, sorting, comparing).
Futher, "Pixel-by-Pixel" Comparison: While this sounds technical, but this limitation is interpreted this as a standard algorithmic comparison that is not inherently limited to a specific, novel machine. Simply put, these limitation merely describe sorting, matching and deteriming whether target object bound to the at one first image qualifies to compare a targeted display resource on search result to provide and meet the advertisement requirement , which is clearly a business arrangement in its purest form. Claims 1, 3, and 5-16 merely provide additional abstract concepts and narrow the abstract idea of claim 1. Further, claims 1, 3, and 5-16 are recited at such a high level that the claimed steps amount to no more than a mental processes, such as concepts performed in the human mind (including an observation, evaluation, judgment, opinion) because a human can determine matching results and performs a similarity comparison.
Step 2A-Prong 2: The only additional elements in independent claims 8, 12 and 13 is some form of computerized system. These computerized systems are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of processing data and a generic memory storing data) such that it amounts no more adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f).
Further, Generic Computer Functionality: The claim likely relies on "generic computer components" to perform the sorting and comparison rather than a specific improvement in how the computer operates.
Step 2B: The claim does not include additional elements that are sufficient to amount to
significantly more than the judicial exception. As discussed above with respect to integration of
the abstract idea into a practical application, the additional element of using the claimed
computer systems amount to no more than “apply” a selection of content on the systems.
Furter, the provided claimed language is likely to be found ineligible in Step 2B because the additional elements (using a computer to perform the comparison and display) are likely considered well-understood, routine, and conventional activities.
The claim does not specify any unconventional technology or a specific, improved technical solution to a problem inherent in computer technology (e.g., an improved image processing algorithm that produces a "technically improved digital image" as opposed to simply using an existing one for an abstract purpose like advertising).
Merely performing the abstract idea on a generic computer is not enough to provide an inventive concept.
Examiner note: , the claims are rejected under § 101 because it is directed to the abstract concept of using image comparison to target advertisements, and the implementation is described at a high level of generality using conventional computing steps. To overcome such a rejection, the claims would likely need to be amended to focus on a specific, non-abstract technological improvement, for example, a novel and unconventional method for image feature extraction or comparison that enhances the underlying technology itself, rather than just using it for a business purpose.
Claim Rejections - 35 USC § 103
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.
Claim(s) 1, 3, 5-6, 8-10 and 12-16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sheng et al (US Pub., No., 2021/04065549 A1) in view of Kambhamettu et al (US Pub., 2009/0315910 A1)
With respect to claims 1, 8 and 9 Sheng teaches a method, a non-transitory computer-readable storage medium, (paragraphs [005] discloses non-transitory computer readable storage medium ) and an electronic device processor and memory (paragraph [0008], discloses an electronic device, including one or mor processors and storage apparatus ) for displaying search results , the method comprising:
determining at least one first key image from a first user for a target object with an advertising requirement(paragraph [0011], discloses determining the label information and the targeted object.., obtain a target to-be-inserted region..));
upon receiving an information search request initiated by a second user based on a second key image comprising a search objects(paragraph [0011], discloses determined from the candidate to -be-inserted region is finally determined from the candidate to be inserted regions, and maximum rectangle searching is performed in the target candidate to-be-inserted ..):
determining matching search results according to the second key image(Fig. 3 & 9, S340 & S907, paragraphs [0006]-[0007] discloses determining a target candidate to-be-implemented regain from the candidate to-be-implanted regions, and perform maximum rectangle searching in the target candidate to-be implanted region to obtain a target to-be-implanted region , paragraph [0011], discloses deteriming from video fragment and object in the targe frame are identified , determining according to the labeling information corrosinding to all objects in the targeted frame, and paragraph [0030] discloses maximum rectangle searching: a manner to deteriming by searching for adjacent pixel point with the same pixel value within a specific region …)and
determining whether the target object shown in each of the at least one first key image and the searched object shown in the second key image belong to a same product category(paragraphs [0030]- [0031], and [0069] discloses maximum rectangle search may be implanted in the following manner: using any pixel point in a target candidate to-be inserted regions as a reference point, and search for adjacent pixel point [second key image] with the same pixel value according to a pixel value of the reference point [second key image belong to a same product category] .., repeating the forgoing operation unit all adjacent pixel point with same pile value are obtained and paragraphs [0070]-[0071], discloses pixel values in the targe to be inserted region are 0 or 1, if pixel value point is 0.., [same category determination] ) ,
performing a similarity comparison between the second key image and the at least one first key image by performing a pixel-by-pixel comparison of a main image region of the second key image showing the searched object and a main image region of the at least one first key image showing the target object (paraph [0047], discloses similarity identification is performed herein, similarity comparison may be performed on each pixel in two adjacent image frames.., similarities between pixels are compared one by one, and paragraph [0048], discloses performing similarity identification of the targe feature of adjacent image frames .. )to determine a degree of match between the second key image and the at least one first key image, wherein the pixel-by-pixel comparison includes the first attribute when the first attribute is determined to be the key attribute, and ignores the first attribute or assigns a lower weight to the first attribute when the first attribute is determined not to be the key attribute (paragraphs [0047]- [0048], discloses similarity identification is performed on the large features of adjacent image frames.., performing similarity identification on the target features of adjacent image frames …, calculating a distance [ degree of match] between the target features of the adjacent image frame and performing similarity identification according to distance …., and compare with a preset distance threshold determined a similarity between the adjacent image frees , which the determine less than the preset distance threshold it is determined that the adjacent image frame belong to the same video fragment and when the distance is grater the or equals to the preset distance threshold it is determined that adjacent image belongs to different video fragment [within the scope of ignores the first attribute or assigns a lower weight to the first attribute when the first attribute is determined not to be the key attribute] and paragraph [0060]-[0064], discloses distance between the pixel sets is less than or equal to the preset distance threshold two pixel sets accord to the distance can be managed ); and
based on the degree of match, deteriming whether the target object bound to the at least one first key image qualifies to compete for a target display resource on a search result page displying the matching search results, wherein the targe display resource is provided to meet the advertising requirement displaying the matching search results, wherein the target display resource is provided to meet the advertising requirement (paragraph [0064], discloses a plurality of communicated regions in the target object may be obtained, and these communicated regions are the candidate to-be-inserted regions, , paragraph [0066], discloses plurality of candidate to -be-inserted regions are determined .., candidate to-be-inserted regions not including non-target objects may be selected from the plurality of candidate to-be-inserted regions [first key image qualifies to compete for targe display] and paragraph [0094], discloses determine the target object according to the labeling information, and cluster the target object to obtain a plurality of candidate to-be-inserted regions [displaying the matching results] ).
Sheng teaches the above elements including in response to determining that the target object and the searched object belong to the same product category(paragraph [0072], discloses pixel point that is adjacent to the reference point and has the same pixel value with the reference point, the adjacent pixel point) and the target to-be-inserted region is determined from the target object in combination with color block clustering in a mask and maximum rectangle searching (paragraph [0095]). Sheng failed to teach determining, based on the product category, whether a first attribute of the searched object is a key attribute, the first attribute comprising color.
However, Kambhamettu teaches determining, based on the product category, whether a first attribute of the searched object is a key attribute, the first attribute comprising color(paragraph [0022], discloses first know portion and a sound known portion of an image may be determined .., applying strokes to the image or by deteriming trimap .., each know portion of image may be refer to either foreground o(F) or a background (B) of the image …, paragraph [0030], discloses determines a pixel-pixel similarity between adjacent pixels in the image , the similarity estimator determines pixel-stroke similarity .., the pixel stroke similarity includes a similarity between pixels to the foreground strokes and a similarity to pixels to the background strokes and paragraph [0042], discloses the pixel-stroke similarity measures the color similarity between two pixels (Pi, P 2) and paragraph [0045], dislcies the pixel-stroke similarity measure the color similarity between P1 and p2 are both close to the color of th stroke ). Therefore, it would have been obvious to the one ordinary skill in the art at the time of the claimed invention for determining a key point feature similarity between by calculating a distance [ degree of match] between the target features of the adjacent image frame and performing similarity identification according to distance and for pixel point that is adjacent to the reference point and has the same pixel value with the reference point, the adjacent pixel point of Sheng with a feature that provides pixel-stroke similarity measure the color similarity between P1 and p2 are both close to the color Kambhamettu in order to represent both the foreground and background colors of the pixels whose FC exceeds the thresholds (see, Kambhamettu, paragraph [0072]).
With respect to claim 3, Sheng in view Kambhamettu teaches elements of claim 1, furthermore, Sheng teaches the method further comprising: determining whether a first product object corresponding to a main subject image in the at least one first key image and a second product object corresponding to a main subject image in the second key image belong to the same product category and if they belong to the same product category, the similarity comparison is between the main subject image in the second key image and the main subject image in the at least one first key image (paragraph [0055], discloses advertisement insertion is to be performed on table, an object of which a category is table may be obtained according to the classification information of the object in the labeling information, and paragraph [0108], discloses the similarity identification unit is configured to perform similarity identification on adjacent image frames and segment the to-be insert video according identification result to obtain video fragments).
With respect to claim 5, Sheng in view Kambhamettu teaches elements of claim 3, furthermore, Sheng teaches the method , determining whether the target object bound to the at least one first key image qualifies to compete for a target display resource on a search result page displaying the matching search results comprises: if the degree of match between the second key image and at least one first key image meets a preset condition, performing a similarity comparison between the second key image and a representative image associated with the target object bound to the at least one first key image; and if a comparison result meets the preset condition, determining that the target object bound to the at least one first key image qualifies to compete for the target display resource on the search result page(paragraphs [0047]- [0048], discloses similarity identification is performed on the large features of adjacent image frames.., performing similarity identification on the target features of adjacent image frames …, calculating a distance [ degree of match] between the target features of the adjacent image frame and performing similarity identification according to distance …., and compare with a preset distance threshold determined a similarity between the adjacent image frees , which the determine less than the preset distance threshold it is determined that the adjacent image frame belong to the same video fragment and when the distance is grater the or equals to the preset distance threshold it is determined that adjacent image belongs to different video fragment [within the scope and paragraph [0060]-[0064], discloses distance between the pixel sets is less than or equal to the preset distance threshold two pixel sets accord to the distance can be managed ).
With respect to claim 6, Sheng in view Kambhamettu teaches elements of claim 5, furthermore, Sheng teaches the method the target object includes a product object, and the representative image associated with the target object includes the main image of the product object(paragraph [0093], discloses an advertisement of a drink of a brand is inserted .., may be 3D model including a drink propaganda poster [product object] ..).
With respect to claims 10, 12 and 13 Sheng teaches an advertising placement method, a non-transitory computer-readable storage medium(paragraphs [0005] discloses non-transitory computer readable storage medium) configured with instructions executable by one or more processor (paragraph [0009], discloses non-transitory computer-readable storage medium, storing instructions which when executed by at least one processor cause the at least one processor to perform the method) and an electronic device comprising one or more processor(paragraph [0008], discloses an electronic device, including one or mor processors and storage apparatus ); and one or more computer-readable memories coupled to the one or more processors and having instructions stored thereon that are executable by the one or more processors to perform, the method(paragraph [0009], discloses non-transitory computer-readable storage medium, storing instructions which when executed by at least one processor cause the at least one processor to perform the method) comprising:
providing an option for configuring a key image within an interface used for configuring an advertisement for a target object (paragraph [0005], discloses detecting and inserting advertising space ); and
receiving at least one first key image submitted by a first user through the provided configuration option(paragraph [0006], discloses maximum rectangle searching is performed);
establishing a binding relationship between the target object and the at least one first key image, so that upon receiving an information search request initiated by a second user based on a second key image comprising a search object, a similarity comparison is performed between the second key image and the at least one first key image to determine a degree of match between the second key image and the at least one first key image wherein the similarity comparison (paragraphs [0030]- [0031], and [0069] discloses maximum rectangle search may be implanted in the following manner: using any pixel point in a target candidate to-be inserted regions as a reference point, and search for adjacent pixel point [second key image] with the same pixel value according to a pixel value of the reference point [second key image belong to a same product category] .., repeating the forgoing operation unit all adjacent pixel point with same pile value are obtained and paragraphs [0070]-[0071], discloses pixel values in the targe to be inserted region are 0 or 1, if pixel value point is 0.., [same category determination] ) , comprises:
determining whether the target object shown in each of the at least one first key image and the searched object shown in the second key image belong to a same product category(paragraphs [0030]- [0031], and [0069] discloses maximum rectangle search may be implanted in the following manner: using any pixel point in a target candidate to-be inserted regions as a reference point, and search for adjacent pixel point [second key image] with the same pixel value according to a pixel value of the reference point [second key image belong to a same product category] .., repeating the forgoing operation unit all adjacent pixel point with same pile value are obtained and paragraphs [0070]-[0071], discloses pixel values in the targe to be inserted region are 0 or 1, if pixel value point is 0.., [same category determination] ) ,
performing a similarity comparison between the second key image and the at least one first key image by performing a pixel-by-pixel comparison of a main image region of the second key image showing the searched object and a main image region of the at least one first key image showing the target object (paraph [0047], discloses similarity identification is performed herein, similarity comparison may be performed on each pixel in two adjacent image frames.., similarities between pixels are compared one by one, and paragraph [0048], discloses performing similarity identification of the targe feature of adjacent image frames .. )to determine a degree of match between the second key image and the at least one first key image, wherein the pixel-by-pixel comparison includes the first attribute when the first attribute is determined to be the key attribute, and ignores the first attribute or assigns a lower weight to the first attribute when the first attribute is determined not to be the key attribute (paragraphs [0047]- [0048], discloses similarity identification is performed on the large features of adjacent image frames.., performing similarity identification on the target features of adjacent image frames …, calculating a distance [ degree of match] between the target features of the adjacent image frame and performing similarity identification according to distance …., and compare with a preset distance threshold determined a similarity between the adjacent image frees , which the determine less than the preset distance threshold it is determined that the adjacent image frame belong to the same video fragment and when the distance is grater the or equals to the preset distance threshold it is determined that adjacent image belongs to different video fragment [within the scope of ignores the first attribute or assigns a lower weight to the first attribute when the first attribute is determined not to be the key attribute] and paragraph [0060]-[0064], discloses distance between the pixel sets is less than or equal to the preset distance threshold two pixel sets accord to the distance can be managed ); and
based on the degree of match, deteriming whether the target object bound to the at least one first key image qualifies to compete for a target display resource on a search result page displying the matching search results, wherein the targe display resource is provided to meet the advertising requirement displaying the matching search results, wherein the target display resource is provided to meet the advertising requirement (paragraph [0064], discloses a plurality of communicated regions in the target object may be obtained, and these communicated regions are the candidate to-be-inserted regions, , paragraph [0066], discloses plurality of candidate to -be-inserted regions are determined .., candidate to-be-inserted regions not including non-target objects may be selected from the plurality of candidate to-be-inserted regions [first key image qualifies to compete for targe display] and paragraph [0094], discloses determine the target object according to the labeling information, and cluster the target object to obtain a plurality of candidate to-be-inserted regions [displaying the matching results] ).
Sheng teaches the above elements including in response to determining that the target object and the searched object belong to the same product category(paragraph [0072], discloses pixel point that is adjacent to the reference point and has the same pixel value with the reference point, the adjacent pixel point) and the target to-be-inserted region is determined from the target object in combination with color block clustering in a mask and maximum rectangle searching (paragraph [0095]). Sheng failed to teach determining, based on the product category, whether a first attribute of the searched object is a key attribute, the first attribute comprising color.
However, Kambhamettu teaches determining, based on the product category, whether a first attribute of the searched object is a key attribute, the first attribute comprising color(paragraph [0022], discloses first know portion and a sound known portion of an image may be determined .., applying strokes to the image or by deteriming trimap .., each know portion of image may be refer to either foreground o(F) or a background (B) of the image …, paragraph [0030], discloses determines a pixel-pixel similarity between adjacent pixels in the image , the similarity estimator determines pixel-stroke similarity .., the pixel stroke similarity includes a similarity between pixels to the foreground strokes and a similarity to pixels to the background strokes and paragraph [0042], discloses the pixel-stroke similarity measures the color similarity between two pixels (Pi, P 2) and paragraph [0045], dislcies the pixel-stroke similarity measure the color similarity between P1 and p2 are both close to the color of th stroke ). Therefore, it would have been obvious to the one ordinary skill in the art at the time of the claimed invention for determining a key point feature similarity between by calculating a distance [ degree of match] between the target features of the adjacent image frame and performing similarity identification according to distance and for pixel point that is adjacent to the reference point and has the same pixel value with the reference point, the adjacent pixel point of Sheng with a feature that provides pixel-stroke similarity measure the color similarity between P1 and p2 are both close to the color Kambhamettu in order to represent both the foreground and background colors of the pixels whose FC exceeds the thresholds (see, Kambhamettu, paragraph [0072]).
With respect to claims 14, 15 and 16 Lui teaches an advertising placement method, a non-transitory computer-readable storage medium(paragraphs [0005] discloses non-transitory computer readable storage medium) configured with instructions executable by one or more processor (paragraph [0009], discloses non-transitory computer-readable storage medium, storing instructions which when executed by at least one processor cause the at least one processor to perform the method) and an electronic device comprising one or more processor(paragraph [0008], discloses an electronic device, including one or mor processors and storage apparatus ); and one or more computer-readable memories coupled to the one or more processors and having instructions stored thereon that are executable by the one or more processors to perform, the method(paragraph [0009], discloses non-transitory computer-readable storage medium, storing instructions which when executed by at least one processor cause the at least one processor to perform the method) the method comprising:
a key image configuration information determination unit, configured to determine at least one first key image configured by a first user for a target object with an advertising requirement (paragraph [0005], discloses detecting and inserting advertising space and paragraph [0006], discloses maximum rectangle searching is performed); and
a key image matching unit, configured to determining matching search results according to the second key image(Fig. 3 & 9, S340 & S907, paragraphs [0006]-[0007] discloses determining a target candidate to-be-implemented regain from the candidate to-be-implanted regions, and perform maximum rectangle searching in the target candidate to-be implanted region to obtain a target to-be-implanted region , paragraph [0011], discloses deteriming from video fragment and object in the targe frame are identified , determining according to the labeling information corrosinding to all objects in the targeted frame, and paragraph [0030] discloses maximum rectangle searching: a manner to deteriming by searching for adjacent pixel point with the same pixel value within a specific region …) upon receiving an information search request initiated by a second user based on a second key image comprising a search object, a similarity comparison is performed between the second key image and the at least one first key image to determine a degree of match between the second key image and the at least one first key image wherein the similarity comparison (paragraphs [0030]- [0031], and [0069] discloses maximum rectangle search may be implanted in the following manner: using any pixel point in a target candidate to-be inserted regions as a reference point, and search for adjacent pixel point [second key image] with the same pixel value according to a pixel value of the reference point [second key image belong to a same product category] .., repeating the forgoing operation unit all adjacent pixel point with same pile value are obtained and paragraphs [0070]-[0071], discloses pixel values in the targe to be inserted region are 0 or 1, if pixel value point is 0.., [same category determination] ) , comprises:
determining whether the target object shown in each of the at least one first key image and the searched object shown in the second key image belong to a same product category(paragraphs [0030]- [0031], and [0069] discloses maximum rectangle search may be implanted in the following manner: using any pixel point in a target candidate to-be inserted regions as a reference point, and search for adjacent pixel point [second key image] with the same pixel value according to a pixel value of the reference point [second key image belong to a same product category] .., repeating the forgoing operation unit all adjacent pixel point with same pile value are obtained and paragraphs [0070]-[0071], discloses pixel values in the targe to be inserted region are 0 or 1, if pixel value point is 0.., [same category determination] ) ,
performing a similarity comparison between the second key image and the at least one first key image by performing a pixel-by-pixel comparison of a main image region of the second key image showing the searched object and a main image region of the at least one first key image showing the target object (paraph [0047], discloses similarity identification is performed herein, similarity comparison may be performed on each pixel in two adjacent image frames.., similarities between pixels are compared one by one, and paragraph [0048], discloses performing similarity identification of the targe feature of adjacent image frames .. )to determine a degree of match between the second key image and the at least one first key image, wherein the pixel-by-pixel comparison includes the first attribute when the first attribute is determined to be the key attribute, and ignores the first attribute or assigns a lower weight to the first attribute when the first attribute is determined not to be the key attribute (paragraphs [0047]- [0048], discloses similarity identification is performed on the large features of adjacent image frames.., performing similarity identification on the target features of adjacent image frames …, calculating a distance [ degree of match] between the target features of the adjacent image frame and performing similarity identification according to distance …., and compare with a preset distance threshold determined a similarity between the adjacent image frees , which the determine less than the preset distance threshold it is determined that the adjacent image frame belong to the same video fragment and when the distance is grater the or equals to the preset distance threshold it is determined that adjacent image belongs to different video fragment [within the scope of ignores the first attribute or assigns a lower weight to the first attribute when the first attribute is determined not to be the key attribute] and paragraph [0060]-[0064], discloses distance between the pixel sets is less than or equal to the preset distance threshold two pixel sets accord to the distance can be managed ); and
based on the degree of match, deteriming whether the target object bound to the at least one first key image qualifies to compete for a target display resource on a search result page displying the matching search results, wherein the targe display resource is provided to meet the advertising requirement displaying the matching search results, wherein the target display resource is provided to meet the advertising requirement (paragraph [0064], discloses a plurality of communicated regions in the target object may be obtained, and these communicated regions are the candidate to-be-inserted regions, , paragraph [0066], discloses plurality of candidate to -be-inserted regions are determined .., candidate to-be-inserted regions not including non-target objects may be selected from the plurality of candidate to-be-inserted regions [first key image qualifies to compete for targe display] and paragraph [0094], discloses determine the target object according to the labeling information, and cluster the target object to obtain a plurality of candidate to-be-inserted regions [displaying the matching results] ).
Sheng teaches the above elements including in response to determining that the target object and the searched object belong to the same product category(paragraph [0072], discloses pixel point that is adjacent to the reference point and has the same pixel value with the reference point, the adjacent pixel point) and the target to-be-inserted region is determined from the target object in combination with color block clustering in a mask and maximum rectangle searching (paragraph [0095]). Sheng failed to teach determining, based on the product category, whether a first attribute of the searched object is a key attribute, the first attribute comprising color.
However, Kambhamettu teaches determining, based on the product category, whether a first attribute of the searched object is a key attribute, the first attribute comprising color(paragraph [0022], discloses first know portion and a sound known portion of an image may be determined .., applying strokes to the image or by deteriming trimap .., each know portion of image may be refer to either foreground o(F) or a background (B) of the image …, paragraph [0030], discloses determines a pixel-pixel similarity between adjacent pixels in the image , the similarity estimator determines pixel-stroke similarity .., the pixel stroke similarity includes a similarity between pixels to the foreground strokes and a similarity to pixels to the background strokes and paragraph [0042], discloses the pixel-stroke similarity measures the color similarity between two pixels (Pi, P 2) and paragraph [0045], dislcies the pixel-stroke similarity measure the color similarity between P1 and p2 are both close to the color of th stroke ). Therefore, it would have been obvious to the one ordinary skill in the art at the time of the claimed invention for determining a key point feature similarity between by calculating a distance [ degree of match] between the target features of the adjacent image frame and performing similarity identification according to distance and for pixel point that is adjacent to the reference point and has the same pixel value with the reference point, the adjacent pixel point of Sheng with a feature that provides pixel-stroke similarity measure the color similarity between P1 and p2 are both close to the color Kambhamettu in order to represent both the foreground and background colors of the pixels whose FC exceeds the thresholds (see, Kambhamettu, paragraph [0072]).
Claim(s) 7, and 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sheng et al (US Pub., No., 2021/04065549 A1) in view of Kambhamettu et al (US Pub., 2009/0315910 A1) and futher view of Cheung et al (US Pub., 2002/0169760 A1)
With respect to claim 7, Sheng in view Kambhamettu teaches elements of claim 1, furthermore, Sheng teaches the method wherein: if a plurality of first key images and their corresponding target objects match the second key image sorting the target objects corresponding to the plurality of first key images (paragraph [0077], dislcies a maximum rectangle searching resulting filtering may be performed on the target to-be-inserted region , paragraph [0078], discloses filtering is performed, paragraphs [0089] , and [0125], discloses filtering can be performed on the target candidate to-be-inserted region ) and Kambhamettu teaches filtering the image (Fig. 2, 202) and controller may also filter image (paragraph [0029]). Sheng and Kambhamettu failed to teach the corrosinding target image sorted based on bid information from the first user for the first key images or premium information for the target display resource, to determine the target object that will obtain the target display resource on the search result page.
However, Cheung teaches based on bid information from the first user for the first key images or premium information for the target display resource, to determine the target object that will obtain the target display resource on the search result page (Fig. 25, 2514, dislcies assign highest-bid/ highest -rank Bid/rank with highest Bid and Fig. 32, 3602, dislcies assign competing Bid = highest active bid at the winner’s ranks exclusive of winning’ bid and paragraph [0241], discloses a sorted lite is formed by sorting all price & place protection search listing.., rank sorting form base ranked to worst ranked, sorted by the bid and third ). Therefore, it would have been obvious to the one ordinary skill in the art before the effective filing date of the claimed invention for filtering can be performed on the target candidate to-be-inserted region of Sheng and r controller may also filter image of Kambhamettu with a feature of on-line marketplace, companies selling products, services, or information bid in an open auction environment for positions on a search result of Cheung in order to promote and increase their web exposure often purchase space on the pages of popular commercial web sites (see, Cheung paragraph [0012]).
With respect to claim 11, Sheng in view Kambhamettu teaches elements of claim 10, but failed to teach further comprising: providing an option for configuring bids individually for each of at least one keywords, and allowing bid configurations to be applied to each keyword through the option.
However, Cheung teaches providing an option for configuring bids individually for each of at least one keywords, and allowing bid configurations to be applied to each keyword through the option (Fig. 25, 2514, discloses assign highest-bid/ highest -rank Bid/rank with highest Bid and Fig. 32, 3602, dislcies assign competing Bid = highest active bid at the winner’s ranks exclusive of winning’ bid and paragraph [0241], discloses a sorted lite is formed by sorting all price & place protection search listing.., rank sorting form base ranked to worst ranked, sorted by the bid and third ). Therefore, it would have been obvious to the one ordinary skill in the art before the effective filing date of the claimed invention for filtering can be performed on the target candidate to-be-inserted region of Sheng and r controller may also filter image of Kambhamettu with a feature of on-line marketplace, companies selling products, services, or information bid in an open auction environment for positions on a search result of Cheung in order to promote and increase their web exposure often purchase space on the pages of popular commercial web sites (see, Cheung paragraph [0012]).
Prior arts:
Sheng et al (US Pub., No., 2021/04065549 A1) discloses a method for detecting an information insertion region is provided. In the method, a video is obtained. The video is segmented to obtain video fragments, each of the video fragments including a subset of image frames in the video. A target frame is obtained in the video fragments.
Kambhamettu et al (US Pub., 2009/0315910 A1) discloses methods and systems for obtaining an alpha matte for an image are disclosed. First and second known portions of an image are determined
Liu et al (US Pub., No., 2021/0174135 A1) discloses embodiments of the present disclosure provide a method of matching image, an apparatus of matching image, a device, and a computer-readable storage medium. The method includes: acquiring an image to be matched; determining a key point feature similarity between any image in an image library and the image to be matched, and determining a color feature similarity between the any image and the image to be matched; determining a fusion similarity between the any image and the image to be matched according to the key point feature similarity and the color feature similarity; and determining whether an image matching the image to be matched exists in the image library or not according to the fusion similarity between each of at least one image in the image library and the image to be matched.
Podilchuk (US Pub., No., 2007/0288453 A1) discloses a system and method of searching multimedia databases using key images that returns image content ranked by degree of similarity to the key-images. A user accesses the search engine via a graphic user interface (GUI) that allows the user to enter key-images using drag-and-drop technology. The user may also enhance the description of the key-images using text-based input, or used text-based input to call up exemplary images.
Cheung et al (US Pub., 2002/0169760 A1) discloses a method and apparatus for managing search listings in a search database include storing one or more search listings for an advertiser. Each search listing includes an associated search term. The system receives from the advertiser identification information for a search listing and a desired rank for the identified search listing, a maximum cost per click for the search listing, or both.
Response to Arguments
Applicant's arguments of 35 U.S.C 101 rejections filed 27 January 2026 have been fully considered but they are not persuasive. Applicants’ augments of as amended claim 1, no longer fits the Office Action’s characterization of the claims are merely “targeting advertising” plus a generic “mental concept” (similarity comprising) is not persuasive. As updated above, the claimed invention is directed to an abstract idea (mental process or mathematical algorithm) without providing a "significantly more" inventive concept. The process of (sorting/comparing items) that can be performed mentally or by a generic computer.
Furthermore, Abstract idea (Step 2A): The steps—determining if objects are in the same category, identifying key attributes (like color), and performing a weighted pixel-by-pixel comparison—are viewed as mental processes (e.g., observing, sorting, comparing).
"Pixel-by-Pixel" Comparison: While this sounds technical, but the claimed limitation interpret this as a standard algorithmic comparison that is not inherently limited to a specific, novel machine.
Generic Computer Functionality: The claim likely relies on "generic computer components" to perform the sorting and comparison rather than a specific improvement in how the computer operates.
Result-Oriented: The claim focuses on the result (matching images based on attributes) rather than the specific technical process of how the image comparison is done, which is a common reason for 101 rejections. Thus, the 35 U.S.C. 101 rejections is maintained.
Applicants’ arguments of claim 1 describes a specific computer-implemented image processing workflow for image-based search that address technical problem arising in based matching and improve the relevance and robustness of search results is not persuasive.
a computer-implemented image-based search workflow the image-based search limitation is directed to an "abstract idea"—such as collecting, analyzing, and displaying data—without providing a specific technological improvement. To overcome this, the workflow must be drafted to focus on a technical solution to a technical problem, rather than just automating a human process.
Furthermore, none of the paragraphs identified in the remark section disclose or provide specific, detailed algorithm for a computer-implemented image processing workflow. The cited disclosure merely describe generalized or result-oriented concept and fail to set forth an image-based process method that address technical problem arising in feature-based matching. Nor do they teach or suggest mechanism that improve the relevance and robustness of search result through concrete computational techniques. Accordingly, the cited material does not demonstrate a specific technological improvement in computer-implemented image processing.
In order to overcome the 35 U.S.C 101 rejections, it is necessary to demonstrate that the invention provides a specific technical improvement.
Applicant's arguments of 35 U.S.C 101 rejections filed 27 January 2026 with respect to claims 1, 3, and 5-16 have been fully considered have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SABA DAGNEW whose telephone number is (571)270-3271. The examiner can normally be reached 9-6:45.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Waseem Ashraf can be reached at (571) 270 -3948. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/SABA DAGNEW/Primary Examiner, Art Unit 3621
Prosecution Insights