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 .
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 10-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 10-12, 9-17 and 19-21 of U.S. Patent No.10,255,703. Although the claims at issue are not identical, they are not patentably distinct from each other because Claim 10 of the currently filed application and claim 1, recite identifying, from a database, one or more common attributes of a category; overlaying two or more images having the one or more common attributes; extracting one or more overlapping areas of the two or more
images; generating a new product image based on the one or more
overlapping areas; and generating a modified new product image by varying attributes of the new product image based on a similarity value measured
between the new product image and at least one image of the two or more images exceeding a threshold.
However, it is noted that the different between Independent claim of the Patent Number is that the currently filed Application discloses identify from a database common attributes; two or more images; and a similarity value measured between the new product image and at least one image of the two or more images exceeding a threshold.
It would have been obvious to one of ordinary skill in the art before
the effective filing date of the claimed invention that the patent discloses col. categories are defined as being contained within a database that contain a plurality of images where each of the images depict an item, therefore Applicant's claimed two or more images is the same as the Patent recited first item and second item. It is further noted that the currently filed Application discloses based on a similarity value measured between the new product image and at least one image of the two or more images exceeding a threshold, whereas the patent discloses based on the different locations as associated with the different physical components of the products in the category defined by the template. It is noted that these attribute identifiers identify the area within the image where each associated extracted common attribute can be placed; and variations to the attributes are added until the similarity value between the created original image is below the similarity threshold value. Therefore, basing on a similarity value measured and basing on a location are each basing on attributes, where the location of the attribute would define a similarity. The difference between the application claims and the patent claim lies in the fact that the patent claim
includes alternative elements that have been described as equivalents.
Therefore, it would have been obvious to substitute the elements of the currently filed Application with the elements of the patented Application, in that the substitution achieves the predictable result of generating a new
modified image with varying attributes of an item of a product.
Claims 10 and 19 of the currently filed Application recite the system
and computer readable storage medium, and are rejected based upon similar rational as above in view of claims 6 and 20, the system and computer readable storage medium of 10255703.
10255703
1. A system comprising: one or more hardware processors and a memory including instructions that, when executed by the one or more hardware processors, causes the one or more hardware processors to perform operations comprising: identifying a template for a category of products, the template defining locations of attributes of products belonging to the category:
identifying common attributes of products of the category based on the template; selecting a first plurality of images from a second larger plurality of images, the first plurality of images selected based on their representation of products having the common attributes; averaging corresponding pixel values across the selected images representing the products having the common attributes; generating an overlaid image representing a new product based on the averaged pixel values; and generating an original image by varying attributes of the new product based on the locations of the attributes defined by the template.
2. The system of claim 1, the operations further comprising altering a visual appearance of an attribute of an object represented by the overlaid image.
3. The system of claim 1, wherein: the varying attributes includes changing a proportion of at least one common attribute of an object represented in the overlaid image.
4. The system of claim 3, wherein: the changing of the proportion of at least one attribute includes at least one of elongating, shortening, widening, or slimming a specific portion of the at least one attribute of the object represented by the overlaid image.
5. The system of claim 1, the operations further comprising: modifying at least one attribute of an object depicted in the overlaid image.
6. The system of claim 1, the operations further comprising: calculating a similarity value between the original image and each of the plurality of images; and varying attributes of an object represented by the original image until the similarity values are below a threshold.
7. The system of claim 1, the operations further comprising eliminating backgrounds from the plurality of images; generating the overlaid image by overlaying the plurality of background-less images; identifying areas from the overlaid image having a density of image information above a predetermined threshold; and generating the original image from the identified areas.
8. The system of claim 7, the operations further comprising excluding areas of the overlaid image having a density of image information below the predetermined threshold from the original image.
9. The system of claim 8, the operations further comprising increasing an area of image overlap by iteratively adjusting an orientation of one or more of the background-less images and overlaying the adjusted images, and generating the base image from the adjusted images.
10. The system of claim 9, the operations further comprising iteratively adjust the orientations until a highest area of image overlap is detected.
11. The system of claim 1, the operations further comprising determine a view angle for objects represented by each of the second plurality of images; and select the plurality of images based on a common view angle of the plurality of images.
18/621579
10. (Currently Amended) A system, comprising: at least one processor; and a memory storing instructions which, when executed by the at least one processor, cause the at least one processor to perform operations including:
receiving a user selection of a category of products;
identifying, from a database, one or more common attributes shared by a plurality of images within the category;
generating a base image by overlaying two or more images of the plurality of images sharing the one or more common attributes, and extracting one or more overlapping areas of the two or more images; and generating an original image by varying attributes of the base image until a similarity value measured between the original image and at least one image of the two or more images falls below a threshold.
11. (Original) The system of claim 10, wherein identifying the one or more common attributes includes identifying the one or more common attributes shared among at least a threshold percentage of the plurality of images based on metadata associated with the plurality of images in the database.
12. (Currently Amended) The system of claim 10, wherein overlaying the two or more images includes determining, for the plurality of images, a quality based on values of saturation, brightness, and contrast calculated for the plurality of images, and the two or more images are selected for overlaying based on the quality metric of the two or more images exceeding a quality threshold.
13. (Original) The system of claim 10, wherein overlaying the two or more images includes overlaying the two or more images based on a template for the category of products defining locations of the products in the category as associated with different attributes of the products in the category.
14. (Currently Amended) The system of claim 13, wherein varying the attributes includes integrating at least one additional attribute from the template into the base image, the at least one additional attribute having been excluded from the one or more common attributes.
15. (Original) The system of claim 13, wherein overlaying the two or more images includes overlaying the two or more images by placing the one or more common attributes of the two or more images at corresponding locations associated with the one or more common attributes as defined by the template.
17. (Currently Amended) The system of claim 13, wherein varying the attributes includes altering a proportion of an attribute in the base image based on a corresponding location associated with the attribute as defined by the template, wherein altering the proportion including lengthening, widening, and/or slimming the attribute.
18. (Currently Amended) The system of claim 10, wherein extracting the one or more overlapping areas includes: extracting item images from the two or more images by removing backgrounds of the two or more images; individually rotating the item images to increase an amount of overlap in the item images; and extracting the one or more overlapping areas of the item images where at least a threshold percentage of the item images overlap.
12. A method comprising: identifying a template for a category of products, the template defining locations of attributes of products in the category; identifying common attributes of products of the category based on the template; selecting a first plurality of images from a second larger plurality of images, the first plurality of images selected due to their representation of products having the common attributes: averaging corresponding pixel values across the selected images representing the products having the common attributes; generating an overlaid image representing a new product based on the averaged pixel values, and generating an original image by varying attributes of the new product based on the locations of the attributes defined by the template, the generating being performed by at least one processor of a machine.
13. The method of claim 12, wherein: the template defines a location of a sleeve on a shirt, wherein the products in the category are shirts, and the varying of attributes of the new product includes varying a length of a sleeve of a new shirt generated based on the averaged pixel values, the altering of the length of the sleeve being based on a location of the sleeve indicated by the template.
14. The method of claim 12, further comprising performing a similarity check by comparing the pixel values of the original image with each of the plurality of images.
15. The method of claim 14, wherein: the performing the similarity check includes: calculating a similarity value between the original image and each of the plurality of images; and where the similarity value is above a similarity threshold, additional variation attributes are added to the generated original image.
16. The method of claim 12, wherein: the generating of the overlaid image further includes: differentiating an item within each of the plurality of images using edge detection, generating an item image without the background for each of the plurality of images; and wherein the generating the overlaid image using the generated item image without the background.
17. The method of claim 16, wherein the operations further comprise: overlaying the item image of each of the plurality of images; and extracting overlapping areas where the number of overlapped items are above a predefined percentage to generate the overlaid image.
18. The method of claim 16, wherein: the generating of the overlaid image includes averaging the pixel value of the generated item image without the background.
1. (Currently Amended) A method, comprising: receiving a user selection of a category of products; identifying, from a database, one or more common attributes shared by a plurality of images within the category;
generating a base image by overlaying two or more images of the plurality of images sharing the one or more common attributes, and extracting one or more overlapping areas of the two or more images; and generating an original image by varying attributes of the base image until a similarity value measured between the e original image and at least one image of the two or more images falls below a threshold.
2. (Original) The method of claim 1, wherein identifying the one or more common attributes includes identifying the one or more common attributes shared among at least a threshold percentage of the plurality of images based on metadata associated with the plurality of images in the database.
3. (Currently Amended) The method of claim 1, wherein overlaying the two or more images includes determining, for the plurality of images, a quality based on values of saturation, brightness, and contrast calculated for the plurality of images, and the two or more images are selected for overlaying based on the quality metric of the two or more images exceeding a quality threshold.
4. (Currently Amended) The method of claim 1, wherein overlaying the two or more images includes detecting items present in the two or more images using one or more edge detection techniques, and individually rotating the two or more images to increase an amount of overlap in the items present in the two or more images.
5. (Original) The method of claim 1, wherein overlaying the two or more images includes overlaying the two or more images based on a template for the category of products defining locations of the products in the category as associated with different attributes of the products in the category.
6. (Original) The method of claim 5, wherein overlaying the two or more images includes overlaying the two or more images by placing the one or more common attributes of the two or more images at corresponding locations associated with the one or more common attributes as defined by the template.
7. (Currently Amended) The method of claim 5, wherein varying the attributes includes integrating at least one additional attribute from the template into the base image, the at least one additional attribute having been excluded from the one or more common attributes.
8. (Currently Amended) The method of claim 5, wherein varying the attributes includes altering a proportion of an attribute in the base image based on a corresponding location associated with the attribute as defined by the template, wherein altering the proportion including lengthening, widening, and/or slimming the attribute.
9. (Original) The method of claim 1, wherein extracting the one or more overlapping areas includes extracting item images from the two or more images by removing backgrounds of the two or more images, and extracting the one or more overlapping areas of the item images where at least a threshold percentage of the item images overlap.
19. A non-transitory machine-readable storage medium comprising instructions that, when executed by one or more processors of a machine, cause the machine to perform operations comprising: identifying common attributes of products of the category based on the template; selecting a first plurality of images from a second larger plurality of images, the first plurality of images selected due to their representation of products having the common attributes; averaging corresponding pixel values across the selected images that represent the products having the common attributes; generating an overlaid image representing a new product based on the averaged pixel values; and generating an original image by varying attributes of the new product based on the locations of the attributes defined by the template.
20. The machine-readable medium of claim 19, the operations further comprising altering a visual appearance of an attribute of an object represented by the overlaid image.
21. The machine-readable medium of claim 19, wherein the operations further comprise: calculating a similarity value between the original image and each of the plurality of images; and varying attributes of an object represented by the original image until the similarity values are below a threshold.
19. (Currently Amended) One or more non-transitory computer readable storage media storing instructions, which when executed by at least one processor, cause the at least one processor to perform operations comprising: receiving a user selection of a category of products; identifying, from a database, one or more common attributes shared by a plurality of images within the category; generating a base image by overlaying two or more images of the plurality of images sharing the one or more common attributes, and extracting one or more overlapping areas of the two or more images; and generating an original image by varying attributes of the original image until a similarity value measured between the original image and at least one image of the two or more images falls below a threshold.
20. (Currently Amended) The one or more non-transitory computer readable storage media of claim 19, wherein overlaying the two or more images includes determining, for the plurality of images, a quality based on values of saturation, brightness, and contrast calculated for the plurality of images, and the two or more images are selected for overlaying based on the quality of the two or more images exceeding a quality threshold.
21. (New) The one or more non-transitory computer readable storage media of claim 19, wherein overlaying the two or more images includes individually rotating the two or more images to increase an amount of overlap between products present in the two or more images.
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 (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 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) s 1-15 and 17-21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Faribault et al., U.S. Patent Publication Number 2011/0078055 A1, in view of Karnos, U.S. Patent Number 10,068,149 B2, in view of Staicut 20140279242, in view of Mitsui, U.S. Patent Number 8,090,192 B2 in view of Spaeth et al., U.S. Patent Publication Number 2014/0101615 A1.
Regarding claim 1, Faribault discloses a method comprising: receiving a user selection of a category of products (paragraph 0144, selection of a category by the user; FIG. 6; paragraph 0145, a category “Shirts & Tops—Sleeveless” was selected in the drop-down menu); identify, from a database, one or more common attributes shared by a plurality of images within the category (paragraph 0145, only key image of sleeveless shirts and tops are displayed in the key image sub-pane; selected key image is used as a search criterion based on which search results are displayed; paragraph 0153, database of key image that may be searched; identify key images as well as search results; identified using the search query and a database of key images; paragraph 0157, may identify a type of cuff, collar, buttons, cut and size of a shir in a key image; search a database where different shirs are classified with corresponding cuff, collar buttons, cuts and sizes); varying attributes (paragraph 0150, each customization may potentially lead to a different visual representation being presented; by customizing a certain aspect of the key image, the key image itself may be replaced by another key image (e.g., from a database of key image) such that although it appears a single key image is being customize, the user is actually cycling through different key images, each having its own characteristics, during customization).
However, it is noted that Faribault discloses a user selection of a category of products, identifies common attributes shared by images within the category, but fails to disclose generating a base image by overlaying two or more images of the plurality of images sharing the one or more common attributes, and extracting one or more overlapping areas of the two or more images; and generating an original image by varying attributes of the base image until a similarity value measured between the original image and at least one image of the two or more images falls below a threshold.
Karnos discloses generating a base image (col. 5, lines 21-22, obtains a base image, where the based image includes certain items), combining two or more images of the plurality of images sharing the one or more common attributes (col. 12, lines 53-54, reference image and the base image are combined) and generating an original image by varying attributes of the base image until a similarity value measured between the original image and at least one image of the two or more images falls below a threshold (col. 5, lines 43-45, combine the target object with the base image to generate a combined image, wherein the target object is modified; col. 6, lines 11-15, set of image characteristics may be related to a particular portion of the base image, such as in circumstance in which the base image includes varying lighting conditions for different objects; col. 14, lines 49-51, perform the comparison of one or more identified objects in the base image with reference images in the repository of images; col. 15, lines 1-5, characteristics for the base image; generate one or more correction factors based on the comparison of image characteristics; and apply the one or more correction factors to the first reference image).
It is noted that Faribault in view of Karnos, Karnos discloses combining two images, but fails to specifically disclose overlaying two or more images.
Staicut discloses receiving a user selection of a category of products (paragraph 0079, receives a user input to try out ONE or MULTIPLE (or more) or all of the displayed (or listed) products); identifying, from a database, one or more common attributes shared by a plurality of images within the category (paragraph 0080, overlay position was previous determined with respect to one of the displayed products or another product in the same category; determines a position for each product image or for one product image (to be used for all other product images in the same product category); extracting areas of the image (paragraph 0056, solid color background can also be used for product extraction from the source image); overlaying two or more images of the plurality of images sharing the one or more common attributes (paragraph 0011, overlaying product images of at least two different products; paragraph 0075, overlay one or more product images on the object image; paragraph 0081, user device overlays each of the ONE, MULTIPLE (or more) or ALL product images; paragraph 0087, multiple try outs of the same or different products, in the same or different categories, can also be performed on the same object image); and varying attributes (paragraph 0076, adjust characteristics of one or more of the overlaid product images on the object image; user device receives adjustment parameters and adjusts the overlay of the one or more product images on the object image).
It is noted that Faribault, Karnos, in view of Staicut, that Staicut discloses extracting, but fail to disclose extracting one or more overlapping areas of the two or more images; and similarity value measured between the original image and at least one image of the two or more images falls below a threshold.
Mistui disclose superposition of design data for single-layer patterns and further disclose extracting one or more overlapping areas of the two or more images (col. 5, lines 4-9, reference image B2 is matched with the image A; coordinates of the matching position are calculated at (Xm2, Ym2)-(255.5, 226.5) (unit: pixel); see also FIG. 8 and FIG. 9, which Examiner interprets as extracted overlapping areas of the two or more images until a matching pixel).
It is noted that Faribault, Karnos, Staicut and Mitsui discloses images, but fail to specifically disclose a similarity value measured between the original image and at least one image of the two or more images falls below a threshold.
Sapeth discloses a similarity value measured between the original image and at least one image of the two or more images falls below a threshold (paragraph 0041, determines if the visual similarity of image A and image B has met a maximum similarity threshold; minimum visual similarity threshold may be 70% similarity and the maximum similarity threshold may be 80%).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include in the selecting of images as disclosed by Faribault, the combined image and base image as disclosed by Karnos, to provide the different key images for customization as disclosed in paragraph 0150, such that although it appears a single key image is being customize, the user is actually cycling through different key images, each having its own characteristics, during customization.
It further would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include in the customization of different key images cycled as disclosed by Faribault, the combined image as disclosed by Karnos, as the overlaying of multiple products as disclosed by Staicut, having a matching position calculated or extracted area, such that although it appears a single key image is being customize. It would have been obvious to one of ordinary skill in the art to include in the extraction area as disclosed by Staicut, the extraction of overlapping areas as disclosed by Mitsui, to allow inspection of a composited image, to allow a user to view the different key areas as disclosed by Faribault where they cycle during customization. It further would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include in the customization as disclosed by Faribault, the visual similarity as disclosed by Spaeth, to determine the actual visual similarity of the customization created to determine if the combined image actually custom.
Regarding claim 2, Faribault discloses wherein identifying the one or more common attributes includes identifying the one or more common attributes shared among at least a threshold percentage of the plurality of images based on metadata associated with the plurality of images in the database (paragraph 0146, may optionally cause the search results shown in the results sub-pane to be narrowed to only those products available in the selected color or similar colors; see also FIG. 7, more like this; filer by).
Karnos 10068149 col. 6, lines 8-10, set of image characteristics as metadata related to the base image.
Regarding claim 3 and 20, Faribault fails to disclose wherein combining the two or more images includes determining, for the plurality of images, a quality based on values of saturation, brightness, and contrast calculated for the plurality of images, and the two or more images are selected for overlaying based on the quality of the two or more images exceeding a quality threshold.
Karnos discloses wherein combining the two or more images includes determining, for the plurality of images, a quality based on values of saturation, brightness, and contrast calculated for the plurality of images, and the two or more images are selected for combining based on the quality of the two or more images exceeding a quality threshold (col. 3, lines 45-48, image combining function, wherein a reference image containing a target object for a base image is identified, image characteristics for the reference image and for the base image are obtained; col. 8, lines 10-12, digital images have associated image characteristics, such as, for example, brightness, contrast, detail (or spatial resolution), and noise; col. 8, lines 24-25, quality of light energy actually reflected from or transmitted through the object being imaged by the camera; col. 8, lines 43-45, color-space models represent different method of defining color variables, such as hue, saturation, brightness, or intensity and can be arbitrarily modified; col. 12, lines 16-21, pictured under ideal lighting conditions in the reference image; applied later to another image).
Staicut discloses paragraph 0075, overlay one or more product images on the object image; paragraph 0081, user device overlays each of the ONE, MULTIPLE (or more) or ALL product images.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include in the selected images as disclosed by Faribault, identifying the quality threshold for combining image characteristics such as saturation, brightness and contrast as disclosed by Karnos, to ensure pictures under ideal lighting conditions are used to combine with another image, or as disclosed by Staicut overlay one or more images.
Regarding claim 10, it is rejected based upon similar rational as above claim 1. Faribault further discloses a system (102, computing unit), comprising: at least one processor (102, processing unit); and a memory storing instructions (106, program instructions) which, when executed by the at least one processor, cause the at least one processor to perform operations (paragraph 0043).
Regarding claims 19, it is rejected based upon similar rational as above claim 1. Faribault further discloses one or more non-transitory computer readable storage media storing instructions, which when executed by at least one processor, cause the at least one processor to perform operations (paragraph 0042).
Claim(s) 4-9, 13-15 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Faribault, Karnos, Staicut and Mitsui, and Sapeth as applied to claims 1 and 19 above, and further in view of Khafizov, U.S. Patent Number 8,892,594.
Regarding claim 4 and 21, Staicut discloses paragraph 0013, calculating an angle of rotation; paragraph 0081, user device overlays each of the ONE, MULTIPLE (or more) or ALL product images; paragraph 0087, multiple try outs of the same or different products, in the same or different categories, can also be performed on the same object image.
However, it is noted that Faribault, Karnos, Staicut and Mitsui, and Sapeth fail to disclose wherein the two or more images includes detecting items present in the two or more images using one or more edge detection techniques, and individually rotating the two or more images to increase an amount of overlap in the items present in the two or more images.
Khafizov discloses the two or more images includes detecting items present in the two or more images using one or more edge detection techniques, and individually rotating the two or more images to increase an amount of overlap in the items present in the two or more images (col. 9, lines 40-54, estimate closeness of shape M to C; initializing closeness; rotate image M and try to match with C step by step; extract image E consisting of pixels forming edge of M; resize E to match the size of C; we will rotate image M and try to match with C step by step.
It would have been obvious to one of ordinary skill in the before the effective filing date of the claimed invention to include in the overlay and rotating as disclosed by Staicut, increasing an amount of overlap as disclosed by Khafizov, i.e. rotate image M and try to match with C, to estimate closeness.
Regarding claims 5 and 13, Staicut discloses paragraph 0013, calculating an angle of rotation; paragraph 0081, user device overlays each of the ONE, MULTIPLE (or more) or ALL product images; paragraph 0087, multiple try outs of the same or different products, in the same or different categories, can also be performed on the same object image.
It is noted that Faribault, Karnos, Staicut and Mitsui, and Sapeth fail to disclose wherein the two or more images includes overlaying the two or more images based on a template for the category of products defining locations of the products in the category as associated with different attributes of the products in the category.
Khafizov discloses the two or more images includes overlaying the two or more images based on a template for the category of products defining locations of the products in the category as associated with different attributes of the products in the category (col. 9, lines 9-12, grouped into categories; images as shape images of the corresponding categories shape-A, shape-B, shape-C, and shape-D; map that depiction to one of the category shapes; mapping can be done using the “The shape matching algorithm”).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include in the overlay of a product in a category as disclosed by St and 1acut, based on a template, the categories associated with different attributes, as disclosed by Khafizov, to perform image overlaying of objects grouped into categories corresponding to a template such as a shape for a shape matching algorithm.
Regarding claim 6 and 15, Staicut discloses wherein overlaying the two or more images includes overlaying the two or more images by placing the one or more common attributes of the two or more images at corresponding locations associated with the one or more common attributes as defined by the template (paragraph 0075, determines an overlay position and overlays the product image on the object image).
Regarding claim 7 and 14, it is noted that Faribault, Karnos, Staicut and Mitsui, and Sapeth fail to disclose wherein varying the attributes includes integrating at least one additional attribute from the template into the base image, the at least one additional attribute having been excluded from the one or more common attributes.
Khafizov discloses varying the attributes includes integrating at least one additional attribute from the template into the base image, the at least one additional attribute having been excluded from the one or more common attributes (FIG. 7B, 9 inches not available; which Examiner interprets as an additional attribute included but excluded from common attributes).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include in the attributes as disclosed by Staicut, paragraph 0076, adjust characteristics of one or more of the overlaid product images on the object image; user device receives adjustment parameters and adjusts the overlay of the one or more product images on the object image, the attribute previously excluded, i.e., 9 inch options, as disclosed by Khafizov, to allow a user to view certain options that are not available.
Regarding claim 8 and 17, Faribault discloses wherein varying the attributes includes altering a proportion of an attribute in the base image based on a corresponding location associated with the attribute as defined by the template, wherein altering the proportion including lengthening, widening, and/or slimming the attribute (FIG. 9, size (neck) 16.5).
Staicut discloses paragraph 0076, adjustment parameters can include a position of a product image on the object image, and a size of the product image including height, width and/or length.
Khafizov discloses col. 10, lines 43-47, system will present the suer with available blade length choices; (assume that blade length is one of the attributes describing knifes; particular attribute example is used for illustrative purposes; col. 10, lines 54-59, user can select one of these three categories by pressing in any of the category icons, or he can use the sliding bar and select the exact length by touching the button and sliding it along the sliding bar until the desired length value).
Regarding claim 9 and 18, Faribault discloses wherein extracting the one or more overlapping areas includes extracting item images from the two or more images by removing backgrounds of the two or more images (FIG. 9, paragraph 0151, FIG. 9, the user has clicked on the collar portion of the key image 908 being customized and a pop-up pane 922 displaying various existing collar types is displayed. Also shown in FIG. 9, the various existing collar types may alternatively or additionally be displayed in a side visualization pane 924, or indeed in any other suitable manner).
Staicut 20140279242 paragraph 0054, enabling the filtering out of the background from the product image; paragraph 0056, product images can be filtered to eliminate background.
Khafizov extracting the one or more overlapping areas of the item images where at least a threshold percentage of the item images overlap (paragraph 0076, adjust characteristics of one or more of the overlaid product images on the object image; user device receives adjustment parameters and adjusts the overlay of the one or more product images on the object image (figures 8A and 8B; col. 9, line 30, extract a contour of the image; col. 9, lines 57-58, transform images E and C into binary images and resize E to match the size of C; col. 10, lines 19-25, matching shape of an image to a contour; category shape represented by contour 108 is being compared with the edge of image 102; computing corresponding matching factor; FIG. 8A, 108; and FIG. 8B, 109).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include in the overlaying of images as disclosed by Staicut with the background removed, extracting areas of overlay as disclosed by Khafizov, transform the images into binary images to match the size, which Examiner interprets as a threshold percentage of the item images overlay, to determine a category shape using a corresponding matching fact.
Response to Arguments
Applicant’s arguments, see page 13-17, filed 04/12/2026, with respect to the rejection(s) of claim(s) 1, 2, 4-8, 10, 1, 13-16, 18 and 19 under Faribault in view of Gupta, and claims 2, 13, 20, Faribault in view of Gupta, further in view of Marchesotti; and claims 9 and 18, Faribault in view of Gupta, further in view of Koh have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of claims 1-15 and 17-21 Faribault et al., U.S. Patent Publication Number 2011/0078055 A1, in view of Karnos, U.S. Patent Number 10,068,149 B2, in view of Staicut 20140279242, in view of Mitsui, U.S. Patent Number 8,090,192 B2 in view of Spaeth et al., U.S. Patent Publication Number 2014/0101615 A1; claims 4-9, 13-15 and 17 over Faribault, Karnos, Staicut and Mitsui, and Sapeth further in view of Khafizov, U.S. Patent Number 8,892,594.
Applicant argues the prior art cited Faribault fails to disclose “generating an original image by varying attributes of the base image until a similarity value measured between the original image and at least one image of the two or images falls below a threshold”. Examiner responds Faribault discloses paragraph 0150, each customization may potentially lead to a different visual representation being presented; by customizing a certain aspect of the key image, the key image itself may be replaced by another key image (e.g., from a database of key image) such that although it appears a single key image is being customize, the user is actually cycling through different key images, each having its own characteristics, during customization. Karnos discloses col. 5, lines 43-45, combine the target object with the base image to generate a combined image, wherein the target object is modified; col. 6, lines 11-15, set of image characteristics may be related to a particular portion of the base image, such as in circumstance in which the base image includes varying lighting conditions for different objects; col. 14, lines 49-51, perform the comparison of one or more identified objects in the base image with reference images in the repository of images; col. 15, lines 1-5, characteristics for the base image; generate one or more correction factors based on the comparison of image characteristics; and apply the one or more correction factors to the first reference image, which Examiner interprets as meeting threshold, i.e. correcting factors applied.
Applicant argues the prior art cited Faribault in view of Gupta fail to disclose “generating a base image by overlaying the two or more images of the plurality of images sharing the one or more common attributes, and extracting one or more overlapping areas of the two or more images. Examiner responds Karnos discloses col. 5, lines 43-45, combine the target object with the base image to generate a combined image, wherein the target object is modified; col. 6, lines 11-15, set of image characteristics may be related to a particular portion of the base image, such as in circumstance in which the base image includes varying lighting conditions for different objects; Mitsui discloses(col. 5, lines 4-9, reference image B2 is matched with the image A; coordinates of the matching position are calculated at (Xm2, Ym2)-(255.5, 226.5) (unit: pixel); see also FIG. 8 and FIG. 9, which Examiner interprets as extracted overlapping areas of the two or more images until a matching pixels.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Minsky U.S. Patent Publication Number 20090132943 A1
Minsky discloses paragraph 0062, a customer can therefore browse the merchant side and select items; paragraph 0062, drag them into the collage view for positioning or arranging them according to a desired view.
Kerr 20170098152
Kerr discloses paragraph 0043, remove elements from an image; paragraph 0016 , receive a visual based query; a selection of one or more image from a user device is received; paragraph 0036 , identify visually similar images comprising the one or more attributes; paragraph 0036, modify a first image with attributes from a second image; paragraph 0044, may submit an image that the user would like to replace with attributes from another image.
Mott et al., U.S. Patent Number 9,724,634
Mott discloses col. 12, lines 8-10, receive selection of an item in a catalog; device returns to a product page; col. 12, line 13, user may view a collection of images.
Suleyman et al., U.S. Patent Number 2014/0019431 A1
Suleyman discloses paragraph 0067, receive a user selection of at least one image; paragraph 0050, user may be shown the colors that were identified in the image; paragraph 0063, one the color selection has been made, a user is shown images 54 that are largely made up of that single color; paragraph 0063, the user has selected a second color (yellow and is shown images 56) made up of those two colors in combination; paragraph 0067, process may then combine the selections, add any weighting or filters and send the composite query to the query server.
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.
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MOTILEWA . GOOD JOHNSON
Primary Examiner
Art Unit 2616
/MOTILEWA GOOD-JOHNSON/Primary Examiner, Art Unit 2619
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