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 .
Claim Interpretation
Claims 1-13 are not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the recitations of “memory”, “processor” and “instructions” provide sufficient structure to perform all claimed limitations.
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.
Claims 1 and 8 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding claim 1 as a presentative claim, the 101 analysis is presented below.
Step 1: It is noted that claim 1 recites a system which is an apparatus. Thus, claim 1 is directed to one of statutory categories of invention.
Step 2A Prong 1: Limitations “analyze the color properties of objects within the captured image” and “select target colors or a range of colors from a live camera feed or image” are interpreted as mental steps which can be practically performed in the human mind. A user/human being can just look at the color image then identify/select target colors of the object presented in the image. Thus, these limitations also fall into the “mental process” grouping of abstract idea. Therefore, claim 1 recites an abstract idea.
Step 2A Prong 2: Claim does recite addition limitations/elements “memory”, “processor” and “interface”. These additional limitations/elements are recited at a high level of generality such that they amount to no more than mere instructions to implement the abstract idea on a conventional computer. The claims do not point to a specific improvement in computer itself. The additional elements, taken individually and in combination, do not contribute to an inventive concept.
Step 2B: These additional limitations/elements are recited at a high level of generality such that they amount to no more than mere instructions to implement the abstract idea on a conventional computer. The claims do not point to a specific improvement in computer itself. The additional elements, taken individually and in combination, do not contribute to an inventive concept. These additional limitations/elements do not amount to an integration of the judicial exception into a practical application. Therefore, claim is directed to an abstract idea without significantly more.
Regarding claim 8, the advanced statements as applied to claim 1 above are incorporated herein. It is noted that claim further recites claim limitations “presenting to the user via the user interface objects within the image or series of images that match the selected target color or color range” which is considered to extra post-solution activity and thus do not amount to an integration of the judicial exception into a practical application. Thus, claim is directed to an abstract idea without significantly more.
Claim Rejections - 35 USC § 102
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 (i.e., changing from AIA to pre-AIA ) 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 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.
Claim(s) 1-13 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Natesh et al. (U.S. Pat. No. 11,055,759 B1, referred as Natesh hereinafter).
Regarding claim 1, Natesh teaches a system for identifying and locating objects based on color properties, comprising:
a camera or sensor-enabled device configured to capture images (see figure 1 and col. 3 line 7 – col. 4 line 23 (for example, in lines 10-13 of column 3, it describes that mobile device 102 includes at least one camera 108 that can capture images and video from both sides of the device 102); also see 300 of fig. 3A (camera is included in the device 300 per col. 5 lines 35-36), 320 of fig. 3B (camera is included in the device 320 per col. 6 line 4), 340 of fig. 3C, 360 fig. 3D, 400 of fig. 4A, 420 of fig. 4B, 440 of fig. 4C, 500 of fig. 5A, 520 of fig. 5B, 802 of fig. 8, 1202 of fig. 12, 1402 of fig. 14)
a processor coupled to said camera or sensor-enabled device (see figure 1 and col. 3 line 7 – col. 4 line 23 (for example, in lines 7-28 of column 3, it describes that the interaction between the user and computing device through gestures made on touch screen and running application on the computing device to perform color selection; thus, computing device 102 inherently include a processor in order to perform these functions); image processor 812 of figure 8; processor 1320 of figure 13; col. 19 lines 55-62 (processing unit CPU))
a memory in communication with said processor; wherein said memory stores an image processing algorithm configured to analyze the color properties of objects within the captured images (see figure 1 and col. 3 line 7 – col. 4 line 23 (for example, in lines 7-28 of column 3, it describes that the interaction between the user and computing device through gestures made on touch screen and running application on the computing device to perform color selection; thus, computing device 102 inherently a memory for storing application (image processing algorithm) to perform color selection image match searching); and
a user interface configured to allow a user to select target colors or a range of colors from a live camera feed or image (see figure 1 and col. 3 line 7 – col. 4 line 2 (for example, touch screen in col. 3 line 19; selectable color elements 114 is generated and user selects the color elements 114 in col. 3 lines 24-26; thus, such selected color element is the so-called target colors); col. 6 lines 45-55 (target colors); col. 9 lines 25-27 (user selects color palette which includes a range of colors); col. 24 lines 39-41 (image data is an image or live stream captured by a camera of the computing device)).
Regarding claim 2, Natesh further teaches wherein the image processing algorithm further includes normalization features to account for variations in lighting conditions when analyzing the color properties of objects (see col. 12 lines 34-59: lighting filter).
Regarding claim 3, Natesh further teaches wherein the user interface provides tools for selecting a color range or tolerance in addition to an exact color shade (see col. 14 lines 25-46 (color shades) and col. 12 lines 34-59 (shading data)).
Regarding claim 4, Natesh further teaches comprising a histogram analysis module configured to create a graphical representation of the distribution of colors within the captured image, allowing for identification of subtle color variations within a defined tolerance range (see col. 9 lines 17-47 (color palette histogram; range of colors that are similar to the target color based on color similarity score calculated for each color in relation to the target color (tolerance range)).
Regarding claim 5, Natesh further teaches wherein the processor continuously processes a live feed from the camera, dynamically adjusting target color ranges based on real-time visual feedback (see col. 3 lines 16-28: interaction between device 102 and user to adjust color settings).
Regarding claim 6, Natesh further teaches comprising feedback mechanisms including but not limited to visual highlights, auditory alerts, or vibratory cues to indicate to the user the location of an object matching the specified color or color range (see 910-912 of fig. 9 and col. 12 lines 34-59 (providing matched products on the display for user to view and make a selection); col. 17 lines 25-29 (the use of visual and audio commands for interaction between user and device); with regard to vibration cues, please see 103 rejection below)).
Regarding claim 7, Natesh further teaches wherein the user interface is equipped with manual tools allowing users to specify target colors or color ranges image (see figure 1 and col. 3 line 7 – col. 4 line 2 (for example, touch screen in col. 3 line 19; selectable color elements 114 is generated and user selects the color elements 114 in col. 3 lines 24-26; thus, such selected color element is the so-called target colors); col. 9 lines 25-27 (user selects color palette which includes a range of colors)), and automated tools for selecting target colors or color ranges based on previously saved images (see col. 4 lines 54-67).
Regarding claim 8, the advanced statements as applied to claim 1 above are incorporated herein. Natesh further teaches presenting to the user via the user interface objects within the image or series of images that match the selected target color or color range (providing matched products on the display for user to view and make a selection).
Regarding claim 9, Natesh further teaches comprising the step of normalizing the captured image or series of images to account for variations in lighting conditions before processing the image or series of images through the image processing algorithm (see col. 3 lines 20-23 (adjusting color or light settings); col. 12 lines 34-59 (lighting filter)).
Regarding claim 10, Natesh further teaches wherein the step of processing includes analyzing a histogram of the captured image or series of images to identify multiple shades of the target color or color range (see col. 9 lines 17-47 (color palette histogram; range of colors that are similar to the target color based on color similarity score calculated for each color in relation to the target color)).
Regarding claim 11, Natesh further teaches comprising the step of providing feedback to the user through one or more feedback mechanisms when an object matching the specified color or color range is identified (see 910-912 of fig. 9 and col. 12 lines 34-59 (providing matched products on the display for user to view and make a selection)).
Regarding claim 12, Natesh further teaches wherein the step of presenting includes actively highlighting the matching objects on the user interface to differentiate them from non-matching objects (see 910 of fig. 9 and col. 12 line 34 - col. 13 line 5 (910 provides both matching objects and non-matching objects so user can select matching one. In case of non-matching one, user selects another target color to initiate another search).
Regarding claim 13, Natesh further teaches wherein the histogram analysis module further allows users to save specific color distributions associated with known objects for future searches (see col. 9 lines 48-59 (selected color element is compared with color database to identify similar colors that are presented/displayed to user as a search result, wherein color data comprises previous selected colors by user).
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.
Claim(s) 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Natesh.
The advanced statements as applied to claim 1-5 and 7-13 above are incorporated hereinafter.
Regarding claim 6, Natesh does not teach vibratory cues. However, such vibratory cues are well known in the art (Official Notice). The advantage of using of vibratory cues is to better alert the user and/or get user attention. Therefore, before the effective filing of the instant claim invention, it would have been obvious to one of ordinary skill in the art to incorporate such vibratory cues in combination with Natesh for that reasons.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Thornton et al. (U.S. Pat. App. Pub. No. 20130155229A1) teaches an object detection system (see figure 1 and 19) comprising a plurality of cameras (12 and 14), a processor and memory (para. [0110] and figure 19 (processors 1902 and 1902’; memory 1906; storage 1926), an interface (GUI 24), color selection (para. [0115]), and displaying search results (para. [0116]).
Lee (U.S. Pat. App. Pub. No. 20180268559A1) teaches a method for tracking object in video in real time (abstract) comprising a live camera (para. [0003]), a memory, processing algorithm and processor (para. [0137]), an interface (para. [0141]: input and output interfaces).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DUY M DANG whose telephone number is (571)272-7389. The examiner can normally be reached Monday to Friday from 7:00AM to 3:00PM.
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/DUY M DANG/Primary Examiner, Art Unit 2662