DETAILED ACTION
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 02/19/2026 has been entered.
Response to Amendment
Amendments and response received 02/19/2026 have been entered. Claims 1, 2, 4-13 and 15-22 are currently pending in this application. Claims 1, 13 and 22 have been amended. Amendments and response are addressed hereinbelow.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 03/05/2026 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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.
Claims 1, 4, 7-11, 13, 15, 18 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Ke Chen et al (US 10740891 B1) in view of Victor G. Corrigan et al (US 6522977 B2).
Regarding claim 1, Chen et al discloses a computer system for identifying coating colors using a digital image (Col. 2 lines 7-15 and Col. 39 lines 5-11 system identifies color accuracy of vehicle using digital images), comprising:
one or more processors (Col. 2 lines 27-31);
one or more computer-readable media having stored thereon executable instructions that when executed by the one or more processors configure the computer system to perform (Col. 2 lines 32-33) at least the following:
receive, through a network connection, a user-provided digital image of a vehicle (Col. 2 lines 32-34);
access, within a vehicle template database, one or more vehicle templates, wherein each vehicle template comprises a digital schematic representation of physical viewable characteristics of a vehicle body (Col. 4 lines 14-35);
map at least one conforming vehicle template to the vehicle within the user-provided digital image by line matching (Col. 6 lines 51-66) and automatically adjusting a size of, the digital schematic representation of the at least one conforming vehicle template to align with the vehicle within the user- provided digital image (Col. 10 lines 20-31);
perform a difference calculation between the mapped conforming vehicle template and the vehicle within the user-provided digital image, wherein the difference calculation is compared to a predetermined threshold (Col. 41 lines 57-63);
identify, with an image processing module, a value associated with the vehicle within the user-provided digital image based on the mapping of the at least one conforming vehicle template (Col. 23 lines 54-58); and
calculate a closest match for [the] identified value associated with the vehicle within the user-provided digital image (Col. 23 lines 54-61 identifying best match for pre-defined landmarks based on comparing base object model and received target model) from the one or more associated color codes.
Chen et al fails to explicitly disclose stored vehicle metadata including one or more manufacturer assigned paint color codes and the identified value being a color value associated with the vehicle from the one or more associated color codes.
Corrigan et al, in the same field of endeavor of providing a database of vehicle identifying information for a plurality of vehicles (Abstract), teaches stored vehicle metadata including one or more manufacturer assigned paint color codes (Col. 8 lines 61-Col. 9 lines 5) and the identified value being a color value associated with the vehicle from the one or more associated color codes (Col. 9 lines 45-48 and Col. 10 lines 21-27).
It would have been obvious to one of ordinary skill in the art before the invention was effectively filed for the computer system for identifying coating colors using a digital image as disclosed by Chen et al comprising access, within a vehicle template database, one or more vehicle templates, wherein each vehicle template comprises a digital schematic representation of physical viewable characteristics of a vehicle body to utilize the teachings of Corrigan et al which teaches stored vehicle metadata including one or more manufacturer assigned paint color codes and the identified value being a color value associated with the vehicle from the one or more associated color codes to attain excellent color matching when repairing vehicles by avoiding differences which may be visibly perceptible.
Regarding claim 4, Chen et al discloses the computer system of claim 1 (see rejection of claim 1).
Chen et al fails to explicitly disclose wherein the executable instructions include instructions that are executable to configure the computer system to provide a user the associated metadata comprising the one or more vehicle characteristics.
Corrigan et al teaches configuring the computer system to provide a user the associated metadata comprising the one or more vehicle characteristics (Col. 8 lines 61-Col. 9 lines 5).
It would have been obvious to one of ordinary skill in the art before the invention was effectively filed for the computer system for identifying coating colors using a digital image as disclosed by Chen et al comprising access, within a vehicle template database, one or more vehicle templates, wherein each vehicle template comprises a digital schematic representation of physical viewable characteristics of a vehicle body to utilize the teachings of Corrigan et al which teaches configuring the computer system to provide a user the associated metadata comprising the one or more vehicle characteristics to provide a quick and efficient search process by eliminating needless information.
Regarding claim 7, Chen et al discloses the computer system of claim 1 (see rejection of claim 1), wherein the executable instructions include instructions that are executable to configure the computer system to identify at least one repair area within the user-provided digital image (Col. 30 line 60-Col. 31 line 4).
Regarding claim 8, Chen et al discloses the computer system of claim 7 (see rejection of claim 7), wherein identifying at least one repair area within the user-provided digital image comprises:
detecting the at least one repair area where the mapped at least one conforming vehicle template differs from the vehicle (Col. 6 line 57-Col. 7 line 9 and Col. 7 lines 17-25);
accessing, within a repair template database, one or more repair templates (Col. 5 lines 45-64 wherein the images depicting the changes indicate repair corrective images of damage); and
mapping at least one conforming repair template to the at least one repair area within the user-provided digital image (Col. 11 lines 5-8 and lines 14-19).
Regarding claim 9, Chen et al discloses the computer system of claim 7 (see rejection of claim 7), wherein the executable instructions include instructions that are executable to configure the computer system to:
parse the at least one repair area from the user-provided digital image (Col. 25 lines 8-16 segmented portion of repair area); and
create a modified user-provided digital image by replacing the parsed at least one repair area with visual data from the at least one conforming vehicle template (Col. 25 lines 35-45).
Regarding claim 10, Chen et al discloses the computer system of claim 1 (see rejection of claim 1), wherein the executable instructions include instructions that are executable to configure the computer system to identify image text within the user-provided digital image (Col. 1 lines 15-25).
Regarding claim 11, Chen et al discloses the computer system of claim 1 (see rejection of claim 1), wherein the image processing module comprises a machine learning algorithm (Col. 27 lines 11-19).
Regarding claim 13, Chen et al discloses a computerized method for use on a computer system comprising one or more processors and one or more computer-readable media having stored thereon executable instructions that when executed by the one or more processors configure the computer system to perform a method of identifying coating colors using a digital image (see rejection of claim 1), the method comprising:
receiving, through the network connection, a user-provided digital image of a vehicle (see rejection of claim 1);
accessing, within a vehicle template database, one or more vehicle templates, wherein each vehicle template comprises a digital schematic representation of physical viewable characteristics of a vehicle body and associated metadata including one or more manufacturer assigned paint color codes (see rejection of claim 1);
mapping at least one conforming vehicle template to the vehicle within the user-provided digital image by line matching and automatically adjusting a size of the digital schematic representation of the at least one conforming vehicle template to align with the vehicle within the user-provided digital image (see rejection of claim 1);
performing a difference calculation between the mapped conforming vehicle template and the vehicle within the user-provided digital image, wherein the difference calculation is compared to a predetermined threshold (see rejection of claim 1);
identifying, with an image processing module, a color value associated with the vehicle within the user-provided digital image based on the mapping of the at least one conforming vehicle template (see rejection of claim 1);
calculating a closest match for identified color value associated with the vehicle within the user-provided digital image from the one or more associated color codes (see rejection of claim 1); and
providing a user the calculated closest match (see rejection of claim 1).
Regarding claim 15, Chen et al discloses the computerized method of claim 13 (See rejection of claim 13), further comprising providing a user the associated metadata comprising the one or more vehicle characteristics (see rejection of claim 4).
Regarding claim 18, Chen et al discloses the computerized method of claim 13 (see rejection of claim 13), further comprising identifying at least one repair area within the user-provided digital image (see rejection of claim 7).
Regarding claim 19, Chen et al discloses the computerized method of claim 18 (see rejection of claim 18), wherein identifying at least one repair area within the user-provided digital image comprises:
detecting the at least one repair area where the mapped at least one conforming vehicle template differs from the vehicle (see rejection of claim 8);
accessing, within a repair template database, a database subset of one or more repair templates (see rejection of claim 8); and
mapping at least one conforming repair template to the at least one repair area within the user-provided digital image (see rejection of claim 8).
Regarding claim 20, Chen et al discloses the computerized method of claim 13 (see rejection of claim 13), wherein the executable instructions include instructions that are executable to configure the computer system to:
parse the at least one repair area from the user-provided digital image (see rejection of claim 9); and
create a modified user-provided digital image by replacing the parsed at least one repair area with visual data from the at least one conforming vehicle template (see rejection of claim 9).
Claims 2 and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Chen et al in view of Corrigan et al as applied to claim 1 above, and further in view of Paul Goedhart et al (US 20210034829 A1).
Regarding claim 2, Chen et al discloses the computer system of claim 1 (see rejection of claim 1).
Chen et al fails to explicitly disclose wherein the color value associated with the vehicle is an RGB value.
Goedhart et al, in the same field of endeavor of automotive color matching systems and methods (Abstract), teaches the color value associated with the vehicle is an RGB value (¶ [75]).
It would have been obvious to one of ordinary skill in the art before the invention was effectively filed for the computer system for identifying coating colors using a digital image as disclosed by Chen et al comprising access, within a vehicle template database, one or more vehicle templates, wherein each vehicle template comprises a digital schematic representation of physical viewable characteristics of a vehicle body to utilize the teachings of Goedhart et al which teaches the color value associated with the vehicle is an RGB value to easily analyze variations in the values to determine whether the color is a solid color or a color effect.
Regarding claim 21, Chen et al discloses the computerized method of claim 13 (see rejection of claim 13), wherein identifying, with the image processing module, the one or more vehicle characteristics within the user-provided digital image comprises:
identifying image text within the user-provided digital image (see rejection of claim 10).
Chen et al fails to explicitly disclose translating the identified image text to machine-encoded text using optical character recognition technology.
Goedhart et al teaches translating the identified image text to machine-encoded text using optical character recognition technology (¶ [67]).
It would have been obvious to one of ordinary skill in the art before the invention was effectively filed for the computer system for identifying coating colors using a digital image as disclosed by Chen et al comprising identifying, with an image processing module, a color value associated with the vehicle within the user-provided digital image to utilize the teachings of Goedhart et al which teaches translating the identified image text to machine-encoded text using optical character recognition technology to determine alphanumeric aspects in the image to further distinguish characteristics of vehicles to enhance the user’s search capabilities.
Claims 5, 16 and 22 are rejected under 35 U.S.C. 103 as being unpatentable over Chen et al in view of Corrigan et al as applied to claim 1 above, and further in view of Michael Henry (US 20090295823 A1).
Regarding claim 5, Chen et al discloses the computer system of claim 1 (see rejection of claim 1).
Chen et al fails to explicitly disclose wherein the executable instructions include instructions that are executable to configure the computer system to: receive user feedback that the closest match is incorrect; calculate a color shift profile; and apply the color shift profile to user-provided digital images of vehicles comprising camera and lighting characteristics of the user-provided digital image of the vehicle.
Henry, in the same field of endeavor of color matching repair paint (Abstract), teaches receiving user feedback that the closest match is incorrect (¶ [14]); calculate a color shift profile; and apply the color shift profile to user-provided digital images of vehicles comprising camera and lighting characteristics of the user-provided digital image of the vehicle (¶ [14-18]).
It would have been obvious to one of ordinary skill in the art before the invention was effectively filed for the computer system for identifying coating colors using a digital image as disclosed by Chen et al comprising access, within a vehicle template database, one or more vehicle templates, wherein each vehicle template comprises a digital schematic representation of physical viewable characteristics of a vehicle body to utilize the teachings of Henry which teaches receiving user feedback that the closest match is incorrect; calculate a color shift profile; and apply the color shift profile to user-provided digital images of vehicles comprising camera and lighting characteristics of the user-provided digital image of the vehicle to minimize differences when matching colors and achieve a more accurate output.
Regarding claim 16, Chen et al discloses the computerized method of claim 13 (See rejection of claim 13), further comprising:
receiving user feedback that the calculated closest match is incorrect (see rejection of claim 5);
calculating a color shift profile (see rejection of claim 5); and
applying the color shift profile to user-provided digital images of vehicles comprising camera and lighting characteristics of the user-provided digital image of the vehicle (see rejection of claim 5).
Regarding claim 22, Chen et al discloses a computer program product comprising one or more computer storage media having stored thereon computer-executable instructions that, when executed at a processor, cause a computer system to perform a method (Col. 2 lines 30-33) for identify coating colors using a digital image (see rejection of claim 1), the method comprising:
receiving, through a network connection, a user-provided digital image of a vehicle (see rejection of claim 1);
accessing, within a vehicle template database, one or more vehicle templates, wherein each vehicle template comprises a digital schematic representation of physical characteristics of a vehicle body and associated metadata including one or more manufacturer assigned paint color codes (see rejection of claim 1);
mapping at least one conforming vehicle template to the vehicle within the user-provided digital image by line matching and automatically adjusting a size of, by aligning the digital schematic representation of the at least one conforming vehicle template to align with the vehicle within the user- provided digital image (see rejection of claim 1);
performing a difference calculation between the mapped conforming vehicle template and the vehicle within the user-provided digital image, wherein the difference calculation is compared to a predetermined threshold (see rejection of claim 1);
identifying, with an image processing module, a color value associated with the vehicle within the user-provided digital image based on the mapping of the at least one conforming vehicle template (see rejection of claim 1);
calculating a closest match for identified color value associated with the vehicle within the user-provided digital image from the one or more associated color codes (see rejection of claim 1);
providing a user the calculated closest match (see rejection of claim 1);
receiving user feedback that the calculated closest match is incorrect (see rejection of claim 5);
calculating a color shift profile (see rejection of claim 5); and
applying the color shift profile to user-provided digital images of vehicles comprising camera and lighting characteristics of the user-provided digital image of the vehicle (see rejection of claim 5).
Claims 6 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Chen et al in view of Corrigan et al as applied to claim 1 above, and further in view of Junya Kenmochi et al (JP 2014235523 A).
Regarding claim 6, Chen et al discloses the computer system of claim 1 (see rejection of claim 1).
Chen et al fails to explicitly disclose wherein the executable instructions include instructions that are executable to configure the computer system to: identify that the closest match falls outside a predetermined threshold; and provide a user an indication that the vehicle was likely repainted.
Kenmochi et al, in the same field of endeavor of identifying that the closest match falls outside a predetermined threshold; and provide a user an indication that the vehicle was likely repainted (¶ [26] and ¶ [35] vehicle characteristic value falls outside of predetermined threshold).
It would have been obvious to one of ordinary skill in the art before the invention was effectively filed for the computer system for identifying coating colors using a digital image as disclosed by Chen et al comprising access, within a vehicle template database, one or more vehicle templates, wherein each vehicle template comprises a digital schematic representation of physical viewable characteristics of a vehicle body to utilize the teachings of Kenmochi which teaches identifying that the closest match falls outside a predetermined threshold; and provide a user an indication that the vehicle was likely repainted to provide additional information used in making a more informed decision on subsequent steps needed in vehicle damage repair.
Regarding claim 17, Chen et al disclose the computerized method of claim 13 (see rejection of claim 13), further comprising:
identifying that the closest match falls outside a predetermined threshold (see rejection of claim 6); and
providing the user an indication that the vehicle was likely repainted (see rejection of claim 6).
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Chen et al in view of Corrigan et al as applied to claim 1 above, and further in view of Diego Urdiales Delgado et al (US 20150339390 A1).
Regarding claim 12, Chen et al discloses the computer system of claim 1 (see rejection of claim 1).
Chen et al fails to explicitly disclose wherein the executable instructions include instructions that are executable to configure the computer system to: receive through the network connection, user-derived audio comprising one or more vehicle characteristics; and translate the user-derived audio to machine-encoded text.
Urdiales Delgado et al, in the same field of endeavor of utilizing a search engine to search a database (Abstract), teaches receiving through the network connection, user-derived audio comprising one or more vehicle characteristics; and translate the user-derived audio to machine-encoded text (¶ [71-72]).
It would have been obvious to one of ordinary skill in the art before the invention was effectively filed for the computer system for identifying coating colors using a digital image as disclosed by Chen et al comprising identifying, with an image processing module, a color value associated with the vehicle within the user-provided digital image to utilize the teachings of Urdiales Delgado et al which teaches receiving through the network connection, user-derived audio comprising one or more vehicle characteristics; and translate the user-derived audio to machine-encoded text to speed the search process while promoting system ease of use.
Response to Arguments
Applicant’s arguments with respect to the claims 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
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/JAMARES Q WASHINGTON/Primary Examiner, Art Unit 2681
April 2, 2026
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