DETAILED ACTION
Status of Claims
The following is a final office action in response to the communication filed 3/3/2026.
Claims 1, 3, 5, 7 and 11 have been amended.
Claims 1-11 are currently pending and have been examined.
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 .
Response to Arguments
Applicant’s replacement drawings, filed 3/3/2026, do not completely remedy the deficiencies addressed within the objection to the drawings. The replacement sheet for Figure 1, for example, has been sufficiently modified to ensure that all text is legible (in black and white). However, the replacement sheet for Figure 2a still has text that cannot be read clearly (the light grey text on the light grey background, for example). Examiner suggests that this/these figures be presented in landscape such that the text is larger, adjust the text to be darker and/or adjust the background to be lighter, etc. The objection to the drawings has been upheld and entry of the replacement drawings is denied.
Applicant’s amendments and associated arguments, filed 3/3/2026, with respect to the objection to claim 10 have been fully considered and are persuasive. The objection to the claims has been withdrawn.
Applicant’s amendments and associated arguments, filed 3/3/2026, regarding the rejection of claim 7 under 35 U.S.C. §112b, has been fully considered and are persuasive. The rejection of claim 7 under 35 U.S.C. §112b, has been withdrawn.
Applicant’s amendments and associated arguments, filed 3/3/2026, with respect to the rejection of the claims under 35 U.S.C. §101 have been considered but they are not persuasive.
Applicant argues that the claims do not recite commercial interactions. Examiner respectfully disagrees. The claims recite a commercial interaction (i.e., a process for customizing and ordering a product) and a process for managing relationships or interactions between people (i.e., interactions between a customer and merchant) and are therefore a method of organizing human activity. Examiner notes that the amended claims also recite a mental process (i.e. performing computations and validations based on requirements and parameters, and the presentation of recommendations) which can be performed in the human mind or by a human using pen and paper.
Applicant further argues that the claims integrate the abstract idea into a practical application as they recite specific components for achieving a technical improvement that solves a technical problem. Examiner respectfully disagrees. The prior art problem of reviewing art work (wherein the “manual process was time consuming, prone to error, and frustrating to all involved”) is an abstract problem that does not unique to, or rooted in, technology. In addition, the utilization of a front end (i.e. for receiving input) and a back end (i.e., for processing data), when recited at this level of breadth, merely amounts to generic computing technology for implementing the abstract idea (i.e. extra-solution activity and application of the abstract idea on a generic computing device). "Claiming the improved speed or efficiency inherent with applying the abstract idea on a computer" does not provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015). See MPEP 2106.05(f).
Applicant’s amendments and associated arguments, filed 3/3/2026, with respect to the rejection of claims under 35 U.S.C. §102 have been considered and are addressed below.
Applicant argues that Asbury recites a fundamentally different architecture than the claimed invention. Examiner respectfully disagrees. Asbury, in Figures 1 and 2, clearly establishes a computing environment with an interface that communicates with server having a front end (ordering website accessible via a network interface) and a backend (various computing devices, such as web server, data store and application server, etc.).
Applicant further argues that there is no disclosure in Asbury of a front end converting user-selected parameters together with uploaded artwork into a unified data object and transmitting that object to a separate back end component and that the data in Asbury never moves between architecturally distinct front end and back end components because Asbury's processing occurs locally within a single computing device. Examiner initially notes that In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., a unified data object, architecturally distinct devices) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). Asbury clearly establishes user selection of input parameters (user selection of a template) and uploading an art file (uploaded digital images) via an ordering website (164) , and the processing of said images and templates using application modules (148) accessible via a network (102). Examiner notes that the “front end” is taught by the website accessible via the user interface and the back end is the processing elements (modules) for generating content to be displayed via said website.
Applicant further argues that Asbury does not disclose the back end performing predetermined validations of the input parameters and uploaded artwork based upon a selected product and imprinting method. Examiner respectfully disagrees. In Asbury, the classification of images based on image quality parameters, with the template having a design representative of the digital images within the group conforming to the quality parameter limitations, teaches performing pre-determined validations based on input parameters and uploaded artwork “based on” a selected product (e.g., the template with the virtual orifice(s)) and the imprinting method (e.g., template may be formatted as any print product ultimately produced by finishers 142 a/b, such as photographic print, calendar, mug, poster, t-shirt, mouse pad, quilt, photobook, etc.).
Applicant further argues that Asbury does not generate a response object that includes the results of validation sand recommendations. Examiner notes that Asbury does generate a response object that includes the results of validation (the provision of a populated template) but acknowledges that Asbury does not explicitly disclose a recommendation as recited in the claims. However, this portion of the argument is moot because it does not apply to all of the references being used in the current rejection.
Drawing Objections
The drawings are objected to because they are not of sufficient quality to permit consideration by the Examiner. For example, the text is too small and blurred to be legible.
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
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 1-11 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract concept without significantly more.
Step 1 of the Subject Matter Eligibility Test entails considering whether the claimed subject matter falls within the four statutory categories of patentable subject matter identified by 35 U.S.C. 101: Process, machine, manufacture, or composition of matter.
Claims 1-11 are directed to a method (process), and a system (machine or manufacture), respectively. As such, the claims are directed to statutory categories of invention.
If the claim recites a statutory category of invention, the claim requires further analysis in Step 2A. Step 2A of the Subject Matter Eligibility Test is a two-prong inquiry. In Prong One, examiners evaluate whether the claim recites a judicial exception.
Claims 1 and 5 recites abstract limitations, including those identified in bold below:
1. A method for validating uploaded artwork for customization upon a consumer product that is accessible via an e-commerce platform user interface, comprising: accessing by a remote device through a web-based format a user interface that communicates with at least one server having a front end and a back end, selecting from a plurality of input parameters preprogramed on said user interface for customizing a product, uploading an art file, converting said plurality of input parameters and said uploaded artwork to data on said front end, transmitting said data to said back end which is constructed and arranged to perform predetermined validations of said plurality of input parameters and said uploaded artwork based upon a selected product and imprinting method, transmitting said response object back to said user interface for display of results, wherein said results further include recommendations for solving an identified issues, and wherein a user is presented options for successfully placing a customized product order.
5. A system for validating uploaded artwork for customization upon a consumer product that is accessible via an e-commerce platform user interface, comprising: at least one server constructed and arranged having a front end and back end in communication, said at least one server having a user interface that includes a plurality of predetermined parameters, wherein a consumer can select parameters related to a product from a preloaded database and upload an artwork file, said front end computes an object that includes said plurality of parameters and said artwork file as data, said front end transmits said object to said back end for processing, wherein the processing includes performing a series of computations and validations based on predetermined requirements pf said plurality of parameters and said artwork file based upon a selected product and imprinting method, said back end generates a response object for transmission to said front end, wherein said response object includes the results of validations, wherein said results further include recommendations, and any additional information or recommendations based on said analysis to complete an order.
These limitations, as drafted, are a process that, under its broadest reasonable interpretation, represents a commercial interaction (i.e., a process for customizing and ordering a product) and a process for managing relationships or interactions between people (i.e., interactions between a customer and merchant) and are therefore a method of organizing human activity. More specifically, other than reciting a computing structure, nothing in the claim element precludes the abstract steps recited above from practically being performed by a human. Thus, the claim recites an abstract idea.
The limitations, as drafted, also recite a mental process (i.e. performing computations and validations based on requirements and parameters and the presentation of recommendations) which can be performed in the human mind or by a human using pen and paper.
If the claim recites a judicial exception in step 2A Prong One , the claim requires further analysis in step 2A Prong Two. In step 2A Prong Two, examiners evaluate whether the claim recites additional elements that integrate the exception into a practical application of that exception.
Claims 1 and 5 recite additional elements, including those identified by underlining below:
1. A method for validating uploaded artwork for customization upon a consumer product that is accessible via an e-commerce platform user interface, comprising: accessing by a remote device through a web-based format a user interface that communicates with at least one server having a front end and a back end, selecting from a plurality of input parameters preprogramed on said user interface for customizing a product, uploading an art file, converting said plurality of input parameters and said uploaded artwork to data on said front end, transmitting said data to said back end which is constructed and arranged to perform predetermined validations of said plurality of input parameters and said uploaded artwork based upon a selected product and imprinting method, transmitting said response object back to said user interface for display of results, wherein said results further include recommendations for solving an identified issues, and wherein a user is presented options for successfully placing a customized product order.
5. A system for validating uploaded artwork for customization upon a consumer product that is accessible via an e-commerce platform user interface, comprising: at least one server constructed and arranged having a front end and back end in communication, said at least one server having a user interface that includes a plurality of predetermined parameters, wherein a consumer can select parameters related to a product from a preloaded database and upload an artwork file, said front end computes an object that includes said plurality of parameters and said artwork file as data, said front end transmits said object to said back end for processing, wherein the processing includes performing a series of computations and validations based on predetermined requirements of said plurality of parameters and said artwork file based upon a selected product and imprinting method, said back end generates a response object for transmission to said front end, wherein said response object includes the results of validations, wherein said results further include recommendations, and any additional information or recommendations based on said analysis to complete an order.
The characterization of an e-commerce platform user interface, remote device, and user interface, including the characterization of a web-based format, amounts to merely indicating a field of use or technological environment in which to apply a judicial exception and cannot integrate the judicial exception into a practical application (see MPEP 2106.05(h)).
In addition, the e-commerce platform user interface, remote device, and user interface are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer component.
Furthermore, the interface communication between computing elements and the user interface for receiving, uploading and displaying information amounts to insignificant extra-solution activity that is merely a nominal or tangential addition to the claim, see MPEP 2106.05(g)).
Accordingly, in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
If the additional elements do not integrate the exception into a practical application in step 2A Prong Two, then the claim is directed to the recited judicial exception, and requires further analysis under Step 2B to determine whether they provide an inventive concept (i.e., whether the additional elements amount to significantly more than the exception itself).
As discussed above, the characterization of the e-commerce platform user interface, remote device, and user interface, including the characterization of a web-based format, amounts to merely indicating a field of use or technological environment in which to apply a judicial exception which does not amount to significantly more than the exception itself. (see MPEP 2106.05(h)).
As discussed above, the e-commerce platform user interface, remote device, and user interface are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer component. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea does not provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit).
As discussed above, the interface communication between computing elements and the user interface for receiving, uploading and displaying information amounts to insignificant extra-solution activity. The Versata and OIP Techs court decisions cited in MPEP 2106.05(d)(II) indicate that storing and retrieving data in memory is a well‐understood, routine, conventional function when it is claimed in a merely generic manner (as it is here). The Symantec, TLI, OIP Techs. and buySAFE court decisions cited in MPEP 2106.05(d)(II) indicate that mere receiving or transmitting data over a network is a well‐understood, routine, conventional function when it is claimed in a merely generic manner (as it is here). The Symantec, Internet Patent Corp. court decision cited in MPEP 2106.05(d)(II) indicate that a web browser’s back and forward functionality is a well‐understood, routine, conventional function when it is claimed in a merely generic manner (as it is here). MPEP 2106.05(d)(II), and the cases cited therein, including in Trading Techs. Int’l v. IBG LLC, 921 F.3d 1084, 1093 (Fed. Cir. 2019), and Intellectual Ventures I LLC v. Erie Indemnity Co., 850 F.3d 1315, 1331 (Fed. Cir. 2017), for example, indicated that the mere displaying of data is a well understood, routine, and conventional function. In addition, the specification demonstrates the well-understood, routine, conventional nature of additional elements as it describes the additional elements as well-understood or routine or conventional (or an equivalent term), as a commercially available product, or in a manner that indicates that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy 35 U.S.C. §112(a).
Thus, even when viewed as an ordered combination, nothing in the claims add significantly more (i.e. an inventive concept) to the abstract idea.
The various limitations of claims 2, 6-7 merely further characterize the field of use or technological environment in which to apply a judicial exception (further characterization of the object type and software environment). For the reasons described above with respect to claims 1 and 5, this judicial exception is not meaningfully integrated into a practical application, or significantly more than the abstract idea
The various limitations of claim(s) 3 and 9-10 merely narrow the previously recited abstract idea limitations (further characterization of the analysis and validation processes). For the reasons described above with respect to claims 1 and 5, this judicial exception is not meaningfully integrated into a practical application, or significantly more than the abstract idea
The various limitations of claim(s) 4 and 8 recite the further function of analyzing artwork using vectors. At this level of breadth, the utilization of vectors could be interpreted as an abstract function (either a form of analysis that could be performed by a human using pen and paper or a mathematical application/analysis for measuring distance/length/dimensions). If the vector analysis is specific to the file type, this merely indicates a field of use. For the reasons described above with respect to claims 1 and 5, this judicial exception is not meaningfully integrated into a practical application, or significantly more than the abstract idea
The various limitations of claim(s) 11 further characterize the communication between devices as occurring in real-time. Real-time data gathering and monitoring is an abstract concept identified by the courts in Electric Power Group (see MPEP 2106.04). In addition, the Symantec, TLI, OIP Techs. and buySAFE court decisions cited in MPEP 2106.05(d)(II) indicate that mere receiving or transmitting data over a network is a well‐understood, routine, conventional function when it is claimed in a merely generic manner (as it is here).
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.
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 and 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Asbury et al (US 20170372346) in view of Person et al. (US 2017/0277984A1).
Regarding claim 1, Asbury discloses:
A method for validating uploaded artwork for customization upon a consumer product that is accessible via an e-commerce platform user interface, comprising:
Asbury Fig. 1-3, see below
accessing by a remote device through a web-based format a user interface that communicates with at least one server having a front end and a back end,
Asbury [0018] Referring to the drawings in detail, FIG. 1 shows an exemplary computing environment 100 that may be used to implement any of the processing described herein (e.g., photo lab computing device 113 such as a kiosk, third party computing device 166 such as a mobile computing device, tablet, or desktop computer).
Asbury [0014] display 140 is connected to bus 124 by video interface 126 and provides a user 125 (FIG. 2) with a graphical user interface (GUI) to view, select and order the images as image effects (e.g., print order offering, such as a photobook). The GUI allows the user to enter commands and information into computer 112 using a keyboard 141 and a user interface selection device 143
Asbury Fig. 2, [0019] disclosing an ordering website (see also [0010], [0003])
selecting from a plurality of input parameters preprogramed on said user interface for customizing a product, uploading an art file, converting said plurality of input parameters and said uploaded artwork to data on said front end,
Asbury [0023] System 101 may also include an image-based print product ordering website 164 (i.e., ordering website) in communication with network 102. Ordering website 164 allows a user 125 (e.g., customer) to upload digital images to the website 164 via a third-party computing device 166.
Asbury [0032] As generally selected by user 125 …, the template may be formatted as any print product ultimately produced by finishers 142a, 142b, such as those discussed above, for example, photographic print, calendar, mug, poster, T-shirt, mouse pad, quilt, photobook and the like.
transmitting said data to said back end which is constructed and arranged to perform predetermined validations of said plurality of input parameters and said uploaded artwork based upon a selected product and imprinting methos ,
Asbury [0025] As stated above, image organizing module 148 is stored in system memory 136, and operates to assist in generating and displaying the print product offering using photo lab computing device 113. As best shown with particular reference to FIG. 3, the computer implements algorithmic method of generating and displaying the print product offering using image organizing module 148 comprises optional step 300 to begin preparation of the print product offering by accessing system memory 136 which includes a plurality of digital images which have been uploaded and stored in the system memory 136.
Asbury [0026] In accordance with an aspect of the invention, the method further comprises step 304 which provides for classifying each digital image within the group, or the group as a whole, based on at least one image quality parameter, wherein the classification includes determining whether either conforming or not conforming to the at least one image quality parameter. The image quality parameter is defined as any type of metric(s) that is indicative of the quality of the respective digital image, including, but not limited to, image quality (sharpness, brightness, contrast, saturation, etc.), image size (dimensions represented by pixels and scan lines), image file size (compressed and/or uncompressed), data transfer rates, data transfer durations, image content (e.g., faces, buildings, other classifications), image characteristics and measurements (e.g., image organizer scores)). The image quality parameter may be a predetermined parameter or a parameter that is dynamic depending on one or more characteristics of each digital image or the group of digital images.
Asbury [0027] For example, the image quality parameter may be based on the file size of each digital image that was uploaded from a device 166 connected to media drive 145 (e.g., smart phone, flash memory devices, etc.), from a printed image that is scanned in using scanner 158, or transferred from data storage server 160 to system memory 136 of photo lab computing device 113. If, for example, the file size for a particular digital image is above a certain minimum image size (for example, but not limited to, 2 MB), it is presumed that this digital image is of sufficient quality to be included in the print product offering. Further, the image quality parameter may be based on the cumulative file size of the entire group of digital images as being greater than a predetermined minimum file size (for example, but not limited to, 10 MB), wherein the group of digital images as a whole must be greater than or equal to the predetermined minimum file size in order for the print product offering to be generated and displayed. Also, the image quality parameter may be based on an average image file size, wherein the average image file size for the digital images that are uploaded is calculated, followed by selecting those digital images that are equal to or greater than the average image file size. This aspect is based on the premise that if each digital image or the group meets or exceeds a file size threshold, the digital images are of a certain minimum quality (e.g., resolution) to generate and display a print product offering that can in turn be fulfilled as a quality print product.
Asbury [0031] The method further includes either selecting images in the group which satisfy the limitations based upon the image quality parameter, or removing digital images from the group that fall outside limitations based upon the image quality parameter, at step 306.
Asbury [0032] The method further comprises step 308 of generating an image product template having a design which is generally representative of the digital images within the group conforming to the quality parameter limitations… As generally selected by user 125 or automatically selected by image organizing module 148, the template may be formatted as any print product ultimately produced by finishers 142a, 142b, such as those discussed above, for example, photographic print, calendar, mug, poster, T-shirt, mouse pad, quilt, photobook and the like. Moreover, such templates may comprise a plurality of virtual orifice (not shown) in which a respective digital image may be positioned or incorporated either automatically by image organizing module 148 or by user 125. …
transmitting said response object back to said user interface for display of results, … , and wherein a user is presented options for successfully placing customized product order.
Asbury [0033] The method further comprises displaying the template design as a print product offering on display 140, at step 310. As such, image organizing module 148 may provide the populated template and corresponding design directly via system bus 124 or indirectly via system memory 136. Image organizing module 148 may otherwise provide the populated template and corresponding design to another application module within system memory 136 before the template and design are provided to display 140. Once provided, a GUI image effect of the populated template and corresponding design can be viewed by one or more users 125. This image effect may be in two dimensions or three dimensions, or any other artifact which adequately depicts the populated template and corresponding print product offering for the user 125.
Asbury [0034] The method comprises the optional step 312, which allows user 125 to reorganize at least one digital image within the displayed print product offering. Here, user 125 may enter one or more commands into computer 113 that rearranges the digital images in the template by generally removing certain digital images or moving certain digital images from one orifice to another. In essence, user 125 is given an opportunity to customize the template design before it is incorporated into a print order.
Asbury [0035] The method further comprises step 314, which allows for the template design to being included within a print order. In order to do so, image organizing module 148 typically compiles the computer-executable instructions which embody the template design and transforms these instructions into ones that can be received and read as print orders by the appropriate finishing device 142a, 142b. As explained above, once designated as a print order, the appropriate finishing device 142a, 142b may analyze the instructions to manufacture a print product.
See also:
Asbury [0021] Each of the finishing devices 142a, 142b may be a printing device that is configured for manufacturing a print product that incorporates one or more digital images associated with a print order. A print product can be any type of good that has a selected digital image printed thereon, such as, for example, photographic print, photobook, calendar, mug, poster, T-shirt, mouse pad, quilt, gift cards, canvas prints and the like.
Asbury [0022] Each finishing device 142a, 142b is configured for receiving the print order from the photo lab computing device 113 and in turn manufacturing the print product using information contained or referenced in the print order, including but not limited to the digital images uploaded by the customer, and other aspects of the print product specified by the customer.
Asbury, as shown above, discloses the display of a pre-populated templated for consideration and further manipulation by a user. Person, directed to a system and method for generating custom user designs for selected print mediums (abstract), more explicitly discloses wherein said results further include recommendations for resolving any identified issues (Person [0065] In another aspect, conversion component 120 may apply the contents of the user's source file to a new template to ensure that the project is formatted properly for professional printing (e.g., it may allow printing of the new target design to be altered or optimized for the medium onto which it is being printed without user intervention). In at least one embodiment, the conversion component 120 may generate an alert (e.g., visual, audible, tactile, etc.) to inform the user 602 of any modifications which may be or have been automatically applied to modify (e.g., optimize) the project for a selected printing method/device (e.g., professional printing, user printing, etc.) and/or suggest user modification or approval of actions to improve printing results (e.g., such as described with reference to FIGS. 4-5).
One of ordinary skill in the art at the time of filing would have recognized that utilize recommendations for addressing identified issues as in Person in the product customization process of Asbury would have yielded predictable results and resulted in an improved system capable of facilitating the generation of customized products with improved aesthetic appearance (Person [0005]).
Additionally and/or alternatively, it would have been obvious to one of ordinary skill in the art at the time of filing to utilize recommendations for addresses identified issues as in Person in the product customization process of Asbury because there is a need for an improved method for combining user images with templates within an image product. (Person [0006]).
Regarding claim 3, the combination of Asbury and Person, as shown above, discloses the limitations of claim 1. Asbury further discloses: wherein said back end utilizes a series of computations and validations based on predetermine requirements, to analyze and validate said uploaded artwork based on predetermined requirements.
Asbury [0026] In accordance with an aspect of the invention, the method further comprises step 304 which provides for classifying each digital image within the group, or the group as a whole, based on at least one image quality parameter, wherein the classification includes determining whether either conforming or not conforming to the at least one image quality parameter. The image quality parameter is defined as any type of metric(s) that is indicative of the quality of the respective digital image, including, but not limited to, image quality (sharpness, brightness, contrast, saturation, etc.), image size (dimensions represented by pixels and scan lines), image file size (compressed and/or uncompressed), data transfer rates, data transfer durations, image content (e.g., faces, buildings, other classifications), image characteristics and measurements (e.g., image organizer scores)). The image quality parameter may be a predetermined parameter or a parameter that is dynamic depending on one or more characteristics of each digital image or the group of digital images.
Asbury [0027] For example, the image quality parameter may be based on the file size of each digital image that was uploaded from a device 166 connected to media drive 145 (e.g., smart phone, flash memory devices, etc.), from a printed image that is scanned in using scanner 158, or transferred from data storage server 160 to system memory 136 of photo lab computing device 113. If, for example, the file size for a particular digital image is above a certain minimum image size (for example, but not limited to, 2 MB), it is presumed that this digital image is of sufficient quality to be included in the print product offering. Further, the image quality parameter may be based on the cumulative file size of the entire group of digital images as being greater than a predetermined minimum file size (for example, but not limited to, 10 MB), wherein the group of digital images as a whole must be greater than or equal to the predetermined minimum file size in order for the print product offering to be generated and displayed. Also, the image quality parameter may be based on an average image file size, wherein the average image file size for the digital images that are uploaded is calculated, followed by selecting those digital images that are equal to or greater than the average image file size. This aspect is based on the premise that if each digital image or the group meets or exceeds a file size threshold, the digital images are of a certain minimum quality (e.g., resolution) to generate and display a print product offering that can in turn be fulfilled as a quality print product.
Regarding claim 5, Asbury discloses:
A system for validating uploaded artwork for customization upon a consumer product that is accessible via an e-commerce platform user interface, comprising:
Asbury [0018] Referring to the drawings in detail, FIG. 1 shows an exemplary computing environment 100 that may be used to implement any of the processing described herein (e.g., photo lab computing device 113 such as a kiosk, third party computing device 166 such as a mobile computing device, tablet, or desktop computer).
at least one server constructed and arranged having a front end and back end in communication,
Asbury [0023] Fig. 1-2
said at least one server having a user interface that includes a plurality of predetermined parameters, wherein a consumer can select parameters related to a product from a preloaded database and upload an artwork file,
Asbury [0023] System 101 may also include an image-based print product ordering website 164 (i.e., ordering website) in communication with network 102. Ordering website 164 allows a user 125 (e.g., customer) to upload digital images to the website 164 via a third-party computing device 166.
Asbury [0032] As generally selected by user 125 …the template may be formatted as any print product ultimately produced by finishers 142a, 142b, such as those discussed above, for example, photographic print, calendar, mug, poster, T-shirt, mouse pad, quilt, photobook and the like.
said front end computes an object that includes said plurality of parameters and said artwork file as data, said front end transmits said object to said back end for processing, wherein the processing includes performing a series of computations and validations based on predetermined requirements of said plurality of parameters and said artwork file based upon a selected product and imprinting method,
Asbury [0025] As stated above, image organizing module 148 is stored in system memory 136, and operates to assist in generating and displaying the print product offering using photo lab computing device 113. As best shown with particular reference to FIG. 3, the computer implements algorithmic method of generating and displaying the print product offering using image organizing module 148 comprises optional step 300 to begin preparation of the print product offering by accessing system memory 136 which includes a plurality of digital images which have been uploaded and stored in the system memory 136. The plurality of digital images may include one or more digital images stored in the system memory 136 by user 125, regardless of whether such digital images were selected by user 125 to be included in a print product that is the subject of another print order or not.
Asbury [0026] In accordance with an aspect of the invention, the method further comprises step 304 which provides for classifying each digital image within the group, or the group as a whole, based on at least one image quality parameter, wherein the classification includes determining whether either conforming or not conforming to the at least one image quality parameter. The image quality parameter is defined as any type of metric(s) that is indicative of the quality of the respective digital image, including, but not limited to, image quality (sharpness, brightness, contrast, saturation, etc.), image size (dimensions represented by pixels and scan lines), image file size (compressed and/or uncompressed), data transfer rates, data transfer durations, image content (e.g., faces, buildings, other classifications), image characteristics and measurements (e.g., image organizer scores)). The image quality parameter may be a predetermined parameter or a parameter that is dynamic depending on one or more characteristics of each digital image or the group of digital images.
Asbury [0027] For example, the image quality parameter may be based on the file size of each digital image that was uploaded from a device 166 connected to media drive 145 (e.g., smart phone, flash memory devices, etc.), from a printed image that is scanned in using scanner 158, or transferred from data storage server 160 to system memory 136 of photo lab computing device 113. If, for example, the file size for a particular digital image is above a certain minimum image size (for example, but not limited to, 2 MB), it is presumed that this digital image is of sufficient quality to be included in the print product offering. Further, the image quality parameter may be based on the cumulative file size of the entire group of digital images as being greater than a predetermined minimum file size (for example, but not limited to, 10 MB), wherein the group of digital images as a whole must be greater than or equal to the predetermined minimum file size in order for the print product offering to be generated and displayed. Also, the image quality parameter may be based on an average image file size, wherein the average image file size for the digital images that are uploaded is calculated, followed by selecting those digital images that are equal to or greater than the average image file size. This aspect is based on the premise that if each digital image or the group meets or exceeds a file size threshold, the digital images are of a certain minimum quality (e.g., resolution) to generate and display a print product offering that can in turn be fulfilled as a quality print product.
Asbury [0031] The method further includes either selecting images in the group which satisfy the limitations based upon the image quality parameter, or removing digital images from the group that fall outside limitations based upon the image quality parameter, at step 306.
Asbury [0032] The method further comprises step 308 of generating an image product template having a design which is generally representative of the digital images within the group conforming to the quality parameter limitations… As generally selected by user 125 or automatically selected by image organizing module 148, the template may be formatted as any print product ultimately produced by finishers 142a, 142b, such as those discussed above, for example, photographic print, calendar, mug, poster, T-shirt, mouse pad, quilt, photobook and the like. Moreover, such templates may comprise a plurality of virtual orifice (not shown) in which a respective digital image may be positioned or incorporated either automatically by image organizing module 148 or by user 125. …
said back end generates a response object for transmission to said front end, wherein said response object includes the results of validations, … and any additional information or recommendations based on said analysis to complete an order.
Asbury [0033] The method further comprises displaying the template design as a print product offering on display 140, at step 310. As such, image organizing module 148 may provide the populated template and corresponding design directly via system bus 124 or indirectly via system memory 136. Image organizing module 148 may otherwise provide the populated template and corresponding design to another application module within system memory 136 before the template and design are provided to display 140. Once provided, a GUI image effect of the populated template and corresponding design can be viewed by one or more users 125. This image effect may be in two dimensions or three dimensions, or any other artifact which adequately depicts the populated template and corresponding print product offering for the user 125.
Asbury [0034] The method comprises the optional step 312, which allows user 125 to reorganize at least one digital image within the displayed print product offering. Here, user 125 may enter one or more commands into computer 113 that rearranges the digital images in the template by generally removing certain digital images or moving certain digital images from one orifice to another. In essence, user 125 is given an opportunity to customize the template design before it is incorporated into a print order.
Asbury [0035] The method further comprises step 314, which allows for the template design to being included within a print order. In order to do so, image organizing module 148 typically compiles the computer-executable instructions which embody the template design and transforms these instructions into ones that can be received and read as print orders by the appropriate finishing device 142a, 142b. As explained above, once designated as a print order, the appropriate finishing device 142a, 142b may analyze the instructions to manufacture a print product.
See also:
Asbury [0021] Each of the finishing devices 142a, 142b may be a printing device that is configured for manufacturing a print product that incorporates one or more digital images associated with a print order. A print product can be any type of good that has a selected digital image printed thereon, such as, for example, photographic print, photobook, calendar, mug, poster, T-shirt, mouse pad, quilt, gift cards, canvas prints and the like.
Asbury [0022] Each finishing device 142a, 142b is configured for receiving the print order from the photo lab computing device 113 and in turn manufacturing the print product using information contained or referenced in the print order, including but not limited to the digital images uploaded by the customer, and other aspects of the print product specified by the customer.
Asbury, as shown above, discloses the display of a pre-populated templated for consideration and further manipulation by a user. Person, directed to a system and method for generating custom user designs for selected print mediums (abstract), more explicitly discloses wherein said results further include recommendations, and any additional information or recommendations based on said analysis ( (Person [0065] In another aspect, conversion component 120 may apply the contents of the user's source file to a new template to ensure that the project is formatted properly for professional printing (e.g., it may allow printing of the new target design to be altered or optimized for the medium onto which it is being printed without user intervention). In at least one embodiment, the conversion component 120 may generate an alert (e.g., visual, audible, tactile, etc.) to inform the user 602 of any modifications which may be or have been automatically applied to modify (e.g., optimize) the project for a selected printing method/device (e.g., professional printing, user printing, etc.) and/or suggest user modification or approval of actions to improve printing results (e.g., such as described with reference to FIGS. 4-5).
One of ordinary skill in the art at the time of filing would have recognized that utilize recommendations for addressing identified issues as in Person in the product customization process of Asbury would have yielded predictable results and resulted in an improved system capable of facilitating the generation of customized products with improved aesthetic appearance (Person [0005]).
Additionally and/or alternatively, it would have been obvious to one of ordinary skill in the art at the time of filing to utilize recommendations for addresses identified issues as in Person in the product customization process of Asbury because there is a need for an improved method for combining user images with templates within an image product. (Person [0006]).
Regarding claim 11, the combination of Asbury and Person, as shown above, discloses the limitations of claim 5. Asbury further discloses: wherein said at least one server said front end and said back end communicate in real time
Asbury [0002] One method of generating an image-based print order is through the use of a photo lab computing device, such as a kiosk. A kiosk is typically located within a mass retail store, supermarket, drug store, or other convenient locations, and allows a customer to upload one or more digital images and generate a print order to manufacture a print product, such as a photo gift. Additional print product offerings may also be automatically created, displayed to the customer, and made available as an additional print order for upsell purposes (i.e., upsell products) as a stand-alone order, to supplement the customer generated print order, or as an upgrade or other type of add-on to the print product that is the subject of the customer generated print order. The print products identified in the selected print orders can then be fulfilled by a product finishing device within the kiosk itself, or by a finishing device in communication with the kiosk through a network, such as the Internet. The finishing device may be located in close proximity to the kiosk or at a remote location.
Claim(s) 2 and 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Asbury et al (US 20170372346), in view of Person et al. (US 2017/0277984A1), in view of Marino (US 20200050157).
Regarding claim 2, the combination of Asbury and Person, as shown above, discloses the limitations of claim 1. Asbury further discloses: wherein said front end creates a …plurality of input parameters and said uploaded art.
Asbury [0023] System 101 may also include an image-based print product ordering website 164 (i.e., ordering website) in communication with network 102. Ordering website 164 allows a user 125 (e.g., customer) to upload digital images to the website 164 via a third-party computing device 166.
Asbury [0032] As generally selected by user 125 …, the template may be formatted as any print product ultimately produced by finishers 142a, 142b, such as those discussed above, for example, photographic print, calendar, mug, poster, T-shirt, mouse pad, quilt, photobook and the like.
Asbury [0025] As stated above, image organizing module 148 is stored in system memory 136, and operates to assist in generating and displaying the print product offering using photo lab computing device 113.
As shown above, Asbury discloses the concept of collecting and transmitting the images and selected template for product generation, but does not explicitly recite the transmission format.
Marino, in a similar field of endeavor, discloses: wherein said front end creates a JavaScript Object Notation (JSON) object that includes said plurality of input parameters and said uploaded art.
Marino [0082] FIG. 5A is an example interface 500 for generating an order specification based on user input provided using the design specification engine 118 via the interface(s) of FIGS. 3A-3H. As shown, the interface 500 is an HTML processor. For example, the user inputs of FIGS. 3A-3H can be captured by the design specification engine 118 of the customer computing device 104 using HTML code 504, which may be supplemented by function calls (e.g., JavaScript function calls 506). Upon detecting user interaction with the go button 502, the digital design engine 138 and/or the design specification engine 118 may generate, based on the data encoded using HTML code 504, the order specification 152 using the functions 506. The order specification 152 can be a text file and/or an electronic message that includes data labels and data values in a format decodable by the digital design engine 138 through the web service node 139 (e.g., JSON, REST, SOAP, XML RPC, etc.).
The combination of Asbury and Person discloses the transmission of a data object to the back-end server, but does not explicitly disclose the object structure. Marino discloses that data can be received and decoded using a number of different formats ( [0085] JSON, REST, SOAP, XML RPC, etc.). Subsequently it would be obvious to substitute the data format of Marino for the data format of Asbury since each individual element and its function are shown in the prior art, albeit shown in separate references, thus, the simple substitution of one known element for another producing a predictable result renders the claim obvious.
Regarding claim 6, the combination of Asbury, Person and Marino, as shown above, discloses the limitations of claim 5. As shown above, Asbury discloses the concept of collecting and transmitting the images and selected template for product generation, but does not explicitly recite the transmission format.
Marino, in a similar field of endeavor, discloses: wherein said front end object created is a JavaScript Object Notation (JSON) object.
Marino [0082] FIG. 5A is an example interface 500 for generating an order specification based on user input provided using the design specification engine 118 via the interface(s) of FIGS. 3A-3H. As shown, the interface 500 is an HTML processor. For example, the user inputs of FIGS. 3A-3H can be captured by the design specification engine 118 of the customer computing device 104 using HTML code 504, which may be supplemented by function calls (e.g., JavaScript function calls 506). Upon detecting user interaction with the go button 502, the digital design engine 138 and/or the design specification engine 118 may generate, based on the data encoded using HTML code 504, the order specification 152 using the functions 506. The order specification 152 can be a text file and/or an electronic message that includes data labels and data values in a format decodable by the digital design engine 138 through the web service node 139 (e.g., JSON, REST, SOAP, XML RPC, etc.).
See claim 2 for rationale to combine.
Claim(s) 4, is/are rejected under 35 U.S.C. 103 as being unpatentable over by Asbury et al (US 20170372346), in view of Person et al. (US 2017/0277984A1), in view of Kostiv et al. (US 20240161363).
Regarding claim 4, the combination of Asbury and Person, as shown above, discloses the limitations of claim 1. Asbury, as shown in claim 1, discloses the concept of analyzing images for a plurality of quality parameters but does not explicitly recite processing based on tracing, vectors and nodes.
Kostiv, in a similar field of endeavor discloses: the step of tracing said uploaded artwork in vectors between nodes.
Kostiv et al. (US 20240161363) Fig. 2 [0032] In some embodiments, the user interface component 210 includes a ruler and guide lines component 212 to control the use of rulers and guide lines for an artboard, a hover mode component 214 to control hover operations for vector graphics application module 200, a last node component 216 to identify a last node of a vector path as part of vector graphics operations for vector graphics application module 200, a help mode component 218 to provide help information to a user of vector graphics application module 200, an auto trace component 220 to enable a user to vectorize an image using vector graphics application module 200
Asbury, Person and Kostiv are each directed to image processing technology. One of ordinary skill in the art at the time of filing would have recognized that applying the tracing technique of Kostiv to the image processing of Asbury and Person would have yielded predictable results and resulted in improved image classification capabilities (abstract) and facilitate further image editing (Kostiv [0010]).
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over by Asbury et al (US 20170372346) in view of Person et al. (US 2017/0277984A1) in view of Williams (US 20080056569).
Regarding claim 7, the combination of Asbury and Person, as shown above, discloses the limitations of claim 5. Asbury, as shown above, discloses wherein said validations are calculated,…, to process and analyze said artwork file (see [0026] and [0027])
While Asbury discloses a series of computations and evaluations, it does not explicitly disclose the utilized programming language or processing environment.
Williams, in the similar field of image processing, discloses that images can be processed using JavaScript, in a graphics processing software environment (see [0114] disclosing images are transferred to an image processor; [0115] The image processor 130 may be executing custom software that may be coded in a variety of programming languages such as C, C++, Objective C, AppleScript, JAVA, JavaScript, HTML, visual basic, or a script language compatible with a commercial image processing software product such as Adobe Photoshop. The customized software may be embodied in a program, a macro, a script, or other suitable software embodiment. ).
It would have been obvious to one of ordinary skill in the art at the time if filing to process images using JavaScript in an Adobe environment, as taught by Williams, in the image processing system of Asbury, in order to effectively facilitate the analysis and classification of images for use in printed products.
Claim(s) 8-9 is/are rejected under 35 U.S.C. 103 as being unpatentable over by Asbury et al (US 20170372346) in view of Person et al. (US 2017/0277984A1) in view of Bowen et al. (US 20220075845).
Regarding claim 8, the combination of Asbury and Person, as shown above, discloses the limitations of claim 5. Asbury, as shown above, discloses wherein the series of computations and validations includes computing set point parameters and boundaries … to perform measurements to validate said artwork.
Asbury [0026] In accordance with an aspect of the invention, the method further comprises step 304 which provides for classifying each digital image within the group, or the group as a whole, based on at least one image quality parameter, wherein the classification includes determining whether either conforming or not conforming to the at least one image quality parameter. The image quality parameter is defined as any type of metric(s) that is indicative of the quality of the respective digital image, including, but not limited to, image quality (sharpness, brightness, contrast, saturation, etc.), image size (dimensions represented by pixels and scan lines), image file size (compressed and/or uncompressed), data transfer rates, data transfer durations, image content (e.g., faces, buildings, other classifications), image characteristics and measurements (e.g., image organizer scores)). The image quality parameter may be a predetermined parameter or a parameter that is dynamic depending on one or more characteristics of each digital image or the group of digital images.
Asbury [0027] For example, the image quality parameter may be based on the file size of each digital image that was uploaded from a device 166 connected to media drive 145 (e.g., smart phone, flash memory devices, etc.), from a printed image that is scanned in using scanner 158, or transferred from data storage server 160 to system memory 136 of photo lab computing device 113. If, for example, the file size for a particular digital image is above a certain minimum image size (for example, but not limited to, 2 MB), it is presumed that this digital image is of sufficient quality to be included in the print product offering. Further, the image quality parameter may be based on the cumulative file size of the entire group of digital images as being greater than a predetermined minimum file size (for example, but not limited to, 10 MB), wherein the group of digital images as a whole must be greater than or equal to the predetermined minimum file size in order for the print product offering to be generated and displayed. Also, the image quality parameter may be based on an average image file size, wherein the average image file size for the digital images that are uploaded is calculated, followed by selecting those digital images that are equal to or greater than the average image file size. This aspect is based on the premise that if each digital image or the group meets or exceeds a file size threshold, the digital images are of a certain minimum quality (e.g., resolution) to generate and display a print product offering that can in turn be fulfilled as a quality print product.
Bowen, in a similar field of endeavor, more explicitly discloses uploaded files may be validated by utilizing vectors to perform measurements.
Bowen [0430] If it is determined that the current stage corresponds to when moderation has been specified to be performed, the process may proceed to block 1610, and the user-provided image may be analyzed to identify objects in the image (e.g., faces, cigarettes, logos, etc.), as similarly discussed elsewhere herein. The objects may be assigned corresponding tags that identify the objects. For example, facial recognition may be performed as described elsewhere herein. Object recognition may be performed using a module configured to generate and extract category independent region proposals (e.g., by generating candidate bounding boxes), using a deep neural network feature extractor configured to extract features from respective candidate regions, and using a classifier (e.g., a Support Vector Machine (SVM) classifier) configured to classify an extracted feature as one of a known class. (see also [0073])
Asbury, Person and Bowen are each directed to image processing technology. One of ordinary skill in the art at the time of filing would have recognized that applying the tracing technique of Bowen to the image processing of Asbury would have yielded predictable results and resulted in improved image classification capabilities for product customization (abstract, [0073])
Regarding claim 9, the combination of Asbury, Person and Bowen, as shown above, discloses the limitations of claim 8. Asbury further discloses: wherein the set point parameters include one of at least size and spacing of said artwork.
Asbury [0026] In accordance with an aspect of the invention, the method further comprises step 304 which provides for classifying each digital image within the group, or the group as a whole, based on at least one image quality parameter, wherein the classification includes determining whether either conforming or not conforming to the at least one image quality parameter. The image quality parameter is defined as any type of metric(s) that is indicative of the quality of the respective digital image, including, but not limited to, image quality (sharpness, brightness, contrast, saturation, etc.), image size (dimensions represented by pixels and scan lines), image file size (compressed and/or uncompressed), data transfer rates, data transfer durations, image content (e.g., faces, buildings, other classifications), image characteristics and measurements (e.g., image organizer scores)). The image quality parameter may be a predetermined parameter or a parameter that is dynamic depending on one or more characteristics of each digital image or the group of digital images.
Asbury [0027] For example, the image quality parameter may be based on the file size of each digital image that was uploaded from a device 166 connected to media drive 145 (e.g., smart phone, flash memory devices, etc.), from a printed image that is scanned in using scanner 158, or transferred from data storage server 160 to system memory 136 of photo lab computing device 113. If, for example, the file size for a particular digital image is above a certain minimum image size (for example, but not limited to, 2 MB), it is presumed that this digital image is of sufficient quality to be included in the print product offering. Further, the image quality parameter may be based on the cumulative file size of the entire group of digital images as being greater than a predetermined minimum file size (for example, but not limited to, 10 MB), wherein the group of digital images as a whole must be greater than or equal to the predetermined minimum file size in order for the print product offering to be generated and displayed. Also, the image quality parameter may be based on an average image file size, wherein the average image file size for the digital images that are uploaded is calculated, followed by selecting those digital images that are equal to or greater than the average image file size. This aspect is based on the premise that if each digital image or the group meets or exceeds a file size threshold, the digital images are of a certain minimum quality (e.g., resolution) to generate and display a print product offering that can in turn be fulfilled as a quality print product.
Claim(s) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over by Asbury et al (US 20170372346), in view of Person et al. (US 2017/0277984A1) in view of Zhang et al. (CN 102789573) (see provided English translation).
Regarding claim 10, the combination of Asbury and Person, as shown above, discloses the limitations of claim 5. Asbury, as shown above, discloses: wherein the series of computations and validations includes analyzing a predetermined [set of requirements].
Asbury [0026] In accordance with an aspect of the invention, the method further comprises step 304 which provides for classifying each digital image within the group, or the group as a whole, based on at least one image quality parameter, wherein the classification includes determining whether either conforming or not conforming to the at least one image quality parameter. The image quality parameter is defined as any type of metric(s) that is indicative of the quality of the respective digital image, including, but not limited to, image quality (sharpness, brightness, contrast, saturation, etc.), image size (dimensions represented by pixels and scan lines), image file size (compressed and/or uncompressed), data transfer rates, data transfer durations, image content (e.g., faces, buildings, other classifications), image characteristics and measurements (e.g., image organizer scores)). The image quality parameter may be a predetermined parameter or a parameter that is dynamic depending on one or more characteristics of each digital image or the group of digital images.
Asbury [0027] For example, the image quality parameter may be based on the file size of each digital image that was uploaded from a device 166 connected to media drive 145 (e.g., smart phone, flash memory devices, etc.), from a printed image that is scanned in using scanner 158, or transferred from data storage server 160 to system memory 136 of photo lab computing device 113. If, for example, the file size for a particular digital image is above a certain minimum image size (for example, but not limited to, 2 MB), it is presumed that this digital image is of sufficient quality to be included in the print product offering. Further, the image quality parameter may be based on the cumulative file size of the entire group of digital images as being greater than a predetermined minimum file size (for example, but not limited to, 10 MB), wherein the group of digital images as a whole must be greater than or equal to the predetermined minimum file size in order for the print product offering to be generated and displayed. Also, the image quality parameter may be based on an average image file size, wherein the average image file size for the digital images that are uploaded is calculated, followed by selecting those digital images that are equal to or greater than the average image file size. This aspect is based on the premise that if each digital image or the group meets or exceeds a file size threshold, the digital images are of a certain minimum quality (e.g., resolution) to generate and display a print product offering that can in turn be fulfilled as a quality print product.
While Asbury discloses a series of computations and evaluations, it does not explicitly disclose the line weight requirements as claimed.
Zhang, in a similar field of endeavor, discloses: analyzing a predetermined positive line weigh requirement and a negative line weight requirement (see [0050], [0066]-[0067], [0084]).
Asbury, Person and Zhang are each directed to the analysis of images. Therefore, one of ordinary skill in the art at the time of filing would have recognized that applying the line weight analysis of Zhang to the image analysis process of Asbury would have yielded predictable results and resulted in an improved system that would allow more efficient target detection (Zhang [0002]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure: Ono et al. (US 6728404).
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
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/ABBY J FLYNN/Examiner, Art Unit 3663
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