DETAILED ACTION
This communication is a Final Office Action on the merits in response to communications received on 01/02/2026. Claims 1 and 11 have been amended. Therefore, claims 1, 5-11, and 15-24 are pending and have been addressed below. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 101
1. 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.
2. Claims 1, 5-11, and 15-24 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Under Step 1 of the two-part analysis from Alice Corp, claim 1 recites a process (a series of acts or steps) and claim 11 recites a machine (a concrete thing, consisting of parts, or of certain devices and combination of devices). Thus, each of the claims fall within one of the four statutory categories.
3. Under Step 2A – Prong One of the two-part analysis from Alice Corp, the claimed invention is directed to an abstract idea.
Claim 1 which is representative of claim 11 recites:
“loading, via a communication or user entry, an image of the physical item including at least one item information of the physical item, the at least one item information including (1) at least one of a manufacturer of the physical item and a product name of the physical item, and (2) at least one of a component classifier, a serial number of the physical item, or a revision numbers of the physical item;”, “when the at least one item information of the physical item is loaded, “performing…image search using the image of the physical item;”, the image of the possible golden image including at least one reference information including (1) at least one of a manufacturer of the possible golden item or a product name of the possible golden item, and (2) at least one of a component classifier, a serial number of the possible golden item, and or revision numbers of the possible golden item;”, “determining a reputation score…;”, “determining whether the at least one reference information is non-textual information;”, “when the at least one reference information is non-textual information, performing…detects and positions image features of the at least one reference information;”, “forming text bounds respectively surrounding the detected image features, tracing at least parts of the physical item in the text bounds, and combining a first one of the text bounds and a second one of the text bounds if the first one of the text bounds is overlapping or within a predetermined proximity of the second one of the text bounds based on the positioning of the detected image features;”, “extracting…text information from the at least one item information and forming a first bill of materials for the at least one item information by…extracting first feature information from the at least one item information;”, “extracting…text information from the at least one reference information according to the text bounds and forming a second bill of materials for the at least one reference information by…extracting second feature information from the text bounds present in the image of the possible golden item;”, “comparing…the first bill of materials and the second bill of materials to determine at least one result that indicates whether the first bill of materials for the at least one item information corresponds to the second bill of materials for the at least one reference information;”, “if it is determined that the first bill of materials for the at least one item information corresponds to the second bill of materials for the at least one reference information, and if the reputation score of the…source is higher than a predetermined threshold, …determines that the physical item is as expected, or if it is determined that the first bill of materials for the at least one item information does not correspond to the second bill of materials for the at least one reference information,…determines that the physical item includes anomalies;”, “generating…an output data with the at least one result, the output data being in a data format;”, “storing…the output data pertaining to the at least one result”
Under the broadest reasonable interpretation, the limitations recite an abstract idea for detecting anomalies using images of physical item(s) which are concepts that encompass fundamental principles or practices (i.e., mitigating risk), a commercial or legal interactions (i.e., legal obligations, sales/marketing activities, business relations), mental processes (i.e., observations, evaluations, judgements, and opinions) that fall within the certain methods of organizing human activity and mental processes groupings of abstract ideas. See MPEP 2106.04
The Applicant’s Specification in at least [009]-[0012] - analyzing microelectronics supply chain provenance/assurance/risks needs to be done in numerous job functions and tasks, for example: supply chain risk managers need to know about risks facing the organization; when outside devices are brought into a secure facility, analysts need to determine whether the device is safe to be used on site; warehouse/logistics staff need to determine whether received products pose a risk or not;
The limitations as a whole recite fundamental economic practices and commercial interactions performed in supply chain monitoring that is used to protect businesses against various risks and to identify deviations from expected product characteristics. The series of steps of “loading”, “performing”, “determining”, “forming”, “extracting”, “comparing”, “generating” and “storing” carry out tasks that involve analyzing product images of physical products that users such as manufacturers normally perform to verify quality, identify manufacturing defects, inconsistencies in appearance, or damage that might otherwise go unnoticed during manual inspection. Next, the limitations involve managing personal behavior or interactions between people because the step of “loading” in the context of the claim encompasses a user providing an image of the physical item for anomaly detection. Lastly, the limitations of [i.e., determining, forming, extracting, comparing, generating], in the context of the claim recite mental process steps for detecting anomalies by collecting information from images and recognizing certain information from the collected information which acts that that may be performed in the human mind or by pen/paper and fall within the mental processes grouping. Therefore, the claim recites an abstract idea.
4. Under Step 2A – Prong Two of the two-part analysis from Alice Corp, this judicial exception is not integrated into a practical application because the additional elements of: “a processor”, “from a data storage”, “a memory”, “via the processor”, “via the processor”, “internet”, “an electronic signal”, “online source”, “from the online source”, “image object/text recognition and/or classification by executing a machine-learning based computer vision algorithm, wherein the machine- leaning based computer vision algorithm”, “automatically or semi-automatically”, “the processor”, “system”, – see claims 1 and 11, are all recited at a high-level of generality in light of the specification. Since the specification describes the additional elements in general terms, without describing the particulars, the additional elements may broadly but reasonably construed as generic computer components being used to perform the judicial exception. Here, the additional elements merely add the words “apply it” with the judicial exception or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea as discussed in MPEP 2106.05 (f).
The other additional elements of: “sending…to retrieve an image of a possible golden item that possibly corresponds to the physical item and/or components thereof… based on a result of the…search”, adds insignificant extra solution to the judicial exception, i.e., (data gathering, data transmission), as discussed in MPEP 2106.05 (g).
The other additional element of: “a method of automating analyzing a physical item without golden reference item, wherein the physical item is a printed circuit board or components on the printed circuit board, and the golden reference item is a known non- abnormal instance of the physical item, the method comprising:”, “a computer-readable” is/are merely an attempt to indicate the field of use or technological environment in which to apply the judicial exception, as discussed in MPEP 2106.05 (h)
Thus, the additional claim elements are not indicative of integration into a practical application, because the claims do not involve improvements to the functioning of a computer, or to any other technology or technical field (MPEP 2106.05(a)), the claims do not apply or use the abstract idea to effect a particular treatment or prophylaxis for a disease or medical condition (Vanda Memo), the claims do not apply the abstract idea with, or by use of, a particular machine (MPEP 2106.05(b)), the claims do not effect a transformation or reduction of a particular article to a different state or thing (MPEP 2106.05(c)), and the claims do not apply or use the abstract idea in some other meaningful way beyond generally linking the use of the abstract idea to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception (MPEP 2106.05(e) and Vanda Memo). Therefore, the claims do not, for example, purport to improve the functioning of a computer. Nor do they effect an improvement in any other technology or technical field. Accordingly, the additional elements do not impose any meaningful limits on practicing the abstract idea and the claims are directed to an abstract idea.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, as discussed above with respect to integration of the abstract idea into a practical application, the additional element(s) of: “a processor”, “from a data storage”, “a memory”, “via the processor”, “via the processor”, “internet”, “an electronic signal”, “online source”, “from the online source”, “image object/text recognition and/or classification by executing a machine-learning based computer vision algorithm, wherein the machine- leaning based computer vision algorithm”, “automatically or semi-automatically”, “the processor”, “system”, – see claims 1 and 11 amount to no more than mere instructions in which to apply the judicial exception and do not provide an inventive concept at Step 2B.
The other additional element of: “sending…to retrieve an image of a possible golden item that possibly corresponds to the physical item and/or components thereof… based on a result of the…search” was considered to be insignificant extra solution activity under Prong Two and must be re-evaluated at Step 2B to determine whether the additional elements are well-understood, routine, and/or conventional.
The Symantec, TLI Communications, Versata and Content Extraction and Transmission, LLC v. Wells Fargo Bank, OIP Techs court decisions cited in MPEP 2106.05(d)(II) further indicate that “receiving or transmitting data over a network” and “electronically scanning or extracting data from a physical document” is/are well-understood, routine, conventional functions when claimed in a generic manner. Therefore, when viewed individually and in combination the additional elements recited in the claim do not provide an inventive concept. The claims are ineligible at Step 2B.
6. Claims 5-10 and 15-24 are dependent of claims 1 and 11.
Claims 5 and 15 recite “wherein the at least one item information/reference information comprises at least one of a make, a model, a serial, a revision, a type, an origin, images, visual images, photographs, non-visual images, x-ray images, terahertz images, electromagnetic images, electroscopic image, specifications, datasheets, item literature, shopping reviews, counterfeit databases, item databases, shop listings, social media information, or news media information.” which further describes the information/data recited in the abstract idea, but does not make the claim any less abstract., Claims 6 and 16 recite “wherein preprocessing both of the at least one item information and the at least one reference information comprises performing one or more of Optical Character Recognition (OCR), text extraction, Natural Language Processing (NLP), image processing, computer vision, image object recognition, textual lookups, textual resolving, and textual auto-complete on both of the at least one item information and the at least one reference information or validating the accuracy of the at least one item information and the at least one reference information” which further describes generic data processing techniques at a high-level of generality and amounts to mere instructions to implement an abstract on a computer – See MPEP 2106.05(f), Claims 7 and 17 recite “wherein comparing the at least one item information and the at least one reference information comprises determining: confidence in identification, source, specification; risk, trust and compliance levels; whether a bill of materials of the physical item is as expected; whether an image of the physical item matches with the at least one reference information; known issues with the physical item; known issues with the bill of materials of the physical item” which further narrows how the abstract idea may be performed, but does not make the claim any less abstract, Claims 8 and 18 recite “wherein comparing the at least one item information and the at least one reference information comprises performing automated and manual analysis on the at least one item information and the at least one reference information” which further narrows how the abstract idea may be performed, but does not make the claim any less abstract, Claims 9 and 19 recite “wherein generating an output data with the at least one result comprises performing one or more of user interface output, report, dashboard, alarm, and notification” which further narrows how the abstract idea may be performed, but does not make the claim any less abstract, Claims 10 and 20 recite “wherein storing an output data with the at least one result comprises storing the output data to a local memory or storage, or transmitting output data to a remote location and storing the output data to a memory at the remote location” which adds insignificant extra-solution activity, i.e., data storage/transmission, as discussed in MPEP 2106.05(g), Claims 21 and 23 recite “wherein the reputation score of the online source is determined based on a reliability of the online source.” which further narrows how the abstract idea may be performed, but does not make the claim any less abstract. Claims 22 and 24 recite “wherein the reliability of the online source is high if the online source is a website of a manufacture of the physical item, medium if the online source is a crowdsourced website, and low if the online source is an unknown website.” which further narrows how the abstract idea may be performed, but does not make the claim any less abstract. Accordingly, when considered individually and in combination with the abstract idea, the limitations recited in the dependent claims do not integrate the abstract idea into a practical application or provide an inventive concept.
Claim Rejections - 35 USC § 103
7. 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.
8. 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.
9. Claim(s) 1, 5-11, 15-20, 21, 23 is/are rejected under 35 U.S.C. 103 as being unpatentable over Stone (US 2018/0101945 A1) in view of Jaquez (2013/0297464 A1) in view of Mao (US 2019/0188729 A1) in further view of Batra (US 2011/0173103 A1).
With respect to claims 1 and 11, Stone discloses
a method and system for automating analyzing a physical item without golden reference item, wherein the physical item is a printed circuit board or components on the printed circuit board, and the golden reference item is a known non- abnormal instance of the physical item (¶ 0021: discloses a system and method for automated model-based inspection system for screening electronic components to detect counterfeit articles. ¶ 0036, 0055, 0123: discloses the system 100 is capable of performing multiple inspection tasks for numerous types of inspections from initial inspection to final inspection. As opposed to simply comparing an image to a database of known “good” images, the system 100 can use a combination of comparison-based, fuzzy logic, and artificial intelligence techniques to make decisions on a case-by-case basis. The combination of these techniques enables the system 100 to inspect various assemblies or parts without a manually entered database of images for comparison. ¶ 0054-0055: discloses the analysis system is able to detect non-conforming electronic components with or without reference to a “golden” or “reference” component, i.e., a known good/authentic component), the method comprising:
loading, via a processor, from a data storage, a memory, or via a communication, or user entry, an image of the physical item including at least one item information of the physical item (¶ 0039, 0042-0043, 0117, 0127: discloses the system includes an imaging system which collects data regarding the electronic components being inspected. Any suitable image(s) can be captured by the imaging system and the data collected by the imaging system is provided to the analysis system which analyzes the data to determine whether the electronic components are potentially non-conforming.),
the at least one item information including (1) at least one of a manufacturer of the physical item and a product name of the physical item (¶ 0047: discloses electronic components, i.e., integrated chips routinely include markings such as manufacturer logos.), and (2) at least one of a component classifier (¶ 0047: discloses electronic components, i.e., integrated chips routinely include markings such as date codes.), a serial number of the physical item (¶ 0047: discloses electronic components, i.e., integrated chips routinely include markings such as part numbers), or a revision numbers of the physical item (¶ 0047: discloses electronic components, i.e., integrated chips routinely include markings such as lot codes);
when the at least one item information of the physical item is loaded (¶ 0039, 0042-0043, 0117, 0127),
the image of the possible golden image including at least one reference information including (1) at least one of a manufacturer of the possible golden item or a product name of the possible golden item (¶ 0047: discloses electronic components, i.e., integrated chips routinely include markings such as manufacturer logos.), and (2) at least one of a component classifier (¶ 0047: discloses electronic components, i.e., integrated chips routinely include markings such as date codes.), a serial number of the possible golden item (¶ 0047: discloses electronic components, i.e., integrated chips routinely include markings such as part numbers), or a revision numbers of the possible golden item (¶ 0047: discloses electronic components, i.e., integrated chips routinely include markings such as lot codes);
the processor determines that the physical item is as expected (¶ 0053, 0111: discloses if the analysis system does not detect a non-conforming component the analysis system provides the component as passed) the processor determines that the physical item includes anomalies (¶ 0055, 0111: discloses excessive variations in the measured characteristics of electronic components are indicative of non-conforming components.)
generating, via the processor, an output data with the at least one result, the output data being in a computer-readable data format (¶ 0089, 0111, 0123, 0126, 0129, 0136: discloses the algorithms employed by the system can provide results in the form of pass/fail/inconclusive which indicate whether non-conformance is suspected. The overall pass/fail/inconclusive indicator for a component could be based on a comparison of the component’s characteristics to one or more reference parts or a comparison of the component’s characteristics to dimensions or tolerances of manufacturer…the analysis system 110 provides a summary report at step 1310); and
storing, via the processor, the output data pertaining to the at least one result in a memory. (¶ 0065, 0125, 0136: discloses analysis results generated by the system 100 could be uploaded to the one or more databases 306 for storage and later use. The database 306 could store historical inspection records 314 which include previous determinations and identify the results of various scans of electronic components.)
The Stone reference does not explicitly disclose the following limitations.
In the same field of endeavor, the Jaquez reference is related to a system and methods for identifying a product through the electronic analysis of aspects of the product by accessing one or more product data resources via an electronic network (¶ 0002) and teaches:
performing, via the processor, Internet image search using the image of the physical item (¶ 0028, 0039, 0041: discloses PDIS 104 includes data retrieval mechanism 216 to obtain product data by crawling websites and via internet screen scraping. PDIS 104 may access product image data that may originate from one or more sources.);
sending, via the processor, an electronic signal to an online source over the internet to retrieve an image of a possible golden item that possibly corresponds to the physical item and/or components thereof from the online source based on a result of the Internet search (¶0039, 0041: discloses PDIS may contact one or more product data sources at step 306 to access product image data. PDIS 104 may access product data in real-time from one or more data sources.),
determining a reputation score of the online source (¶ 0019, 0029, 0032, 0034: discloses the PDIS 104 may include trust-scoring mechanism 220. The trust scoring mechanism may enable PDIS to assign a trust score to one or more product-data sources with which the PDIS has interacted. PDIS may employ trust scoring process in order to enhance its evaluations of product data. A trust score may be assigned to an online merchant system, a bricks and mortar merchant system, etc. An online merchant may be a retailer, vendor, manufacturer.);
determining whether the at least one reference information is non-textual information (¶ 0023, 0029: discloses the PDIS may analyze image data, attribute data in order to identify the product.); when the at least one reference information is non-textual information (¶ 0023, 0029),
performing, via the processor, image object/text recognition and/or classification by executing a machine-learning based computer vision algorithm (¶ 0041: discloses PDIS may employ computer vision technology to analyze and compare received images.), wherein the machine-leaning based computer vision algorithm detects and positions image features of the at least one reference information (¶ 0041: discloses PDIS may identify agreements/disagreements between image data, attribute data, and/or product data. Attribute data may pertain to hundreds of product attributes such color size, weight, features, etc.);and
if the reputation score of the online source is higher than a predetermined threshold (¶ 0029, 0042: discloses a source with a higher trust score may be considered to provide more accurate data. The PDIS may analyze the relevancy and/or reliability of the data sources by comparing the product data obtained from multiple merchant systems. The more often the product data agrees across multiple sources, the more likely it pertains to the received product.)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Stone’s system and methods for screening electronic components, to include the ability for performing, via the processor, Internet image search using the image of the physical item; sending, via the processor, an electronic signal to an online source over the internet to retrieve an image of a possible golden item that possibly corresponds to the physical item and/or components thereof from the online source based on a result of the Internet search; determining a reputation score of the online source; determining whether the at least one reference information is non-textual information; when the at least one reference information is non-textual information; performing, via the processor, image object/text recognition and/or classification by executing a machine-learning based computer vision algorithm, wherein the machine-leaning based computer vision algorithm detects and positions image features of the at least one reference information, as disclosed by Jaquez to achieve the claimed invention. As disclosed by Jaquez, the motivation for the combination would have to provide improvements for accurately identifying a product offered by manufacturers. (¶ 0009)
The combination of Stone and Jaquez does not explicitly disclose the following limitations. In the same field of endeavor, the Mao reference is related to systems and methods for detecting counterfeit products using deep learning (¶ 0002). Mao specifically discloses:
forming text bounds respectively surrounding the detected image features (¶ 0089: discloses each feature map generated may have features corresponding to one or more bounding boxes and labels of the bounding boxes), tracing at least parts of the physical item in the text bounds (¶ 0088: discloses one or more bounding boxes are determined from the image. The locations of the bounding boxes may be defined by x, y coordinate, size, and shape. The information shown in the bounding boxes is a logo label which may include the brand name of the product or specific product name.), and combining a first one of the text bounds and a second one of the text bounds if the first one of the text bounds is overlapping or within a predetermined proximity of the second one of the text bounds based on the positioning of the detected image features (¶ 0090-0091: discloses combine certain overlapping intermediate identifications of the product which may include bounding boxes and their corresponding labels, and bonding boxes having both words and images may be classified as one class);
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combined system and methods of Stone and Jaquez, to include the image feature matching techniques, as disclosed by Mao to achieve the claimed invention. As disclosed by Mao, the motivation of the combination would have been to provide the ability for obtaining consistent features from images of the same product and improved detection accuracy from images of counterfeit products. (¶ 0003-0005, 0073)
The combination of Stone, Jaquez, and Mao does not explicitly disclose the following limitations. In the same field of endeavor, the Batra reference is related to comparing two multi-level bills of material (BOM) structures and a report is generated that displays the results of the comparison in a side by side manner (¶ 0015, 0053) and teaches:
extracting, via the processor, text information from the at least one item information and forming a first bill of materials for the at least one item information by automatically or semi-automatically extracting first feature information from the at least one item information (¶ 0054-0058: discloses identifiers for BOMs (bill or materials) may be received. The comparison structure generator 608 generates the structure that is used in the comparison. A comparison structure is generated based on the hierarchy of the BOM and the configured parameters…based on only certain items. The comparison structure generator determines which information is needed and generates a comparison file with this information. The file may be structured such that that hierarchy of the bill of material is preserved.);
extracting, via the processor, text information from the at least one reference information according to the text bounds and forming a second bill of materials for the at least one reference information by automatically or semi-automatically extracting second feature information from the text bounds present in the image of the possible golden item(¶ 0018-0020, 0054-0058: discloses identifiers for BOMs may be received. The comparison structure generator 608 generates the structure that is used in the comparison. A comparison structure is generated based on the hierarchy of the BOM and the configured parameters…based on only certain items. The comparison structure generator determines which information is needed and generates a comparison file with this information. The file may be structured such that that hierarchy of the bill of material is preserved. The examiner notes more than one comparison file is generated.);
comparing, via the processor, the first bill of materials and the second bill of materials to determine at least one result that indicates whether the first bill of materials for the at least one item information corresponds to the second bill of materials for the at least one reference information (¶ 0018-0023, 0053, 0056-0058); if it is determined that the first bill of materials for the at least one item information corresponds to the second bill of materials for the at least one reference information or if it is determined that the first bill of materials for the at least one item information does not correspond to the second bill of materials for the at least one reference information (¶ 0018-0023, 0053, 0056-0058: discloses the comparison files which represents the first and second bills of materials formed above are compared and the results are provided to a report generator 618 which can generate the report. In one example, an extensible markup language (XML) file is generated for each BOM. Fig. 7 shows multiple XML files that are generated and compared. A comparison file is used to compare the two XML sources files to generate an output XML source file for the report which represents a computer-readable data format. Accordingly, a user may view the report and quickly determine the differences between BOM #1 and BOM #2. The user can quickly look at the report and determine that components are missing or different. The side-by-side comparison allows the determine to be made quickly and easily. The examiner notes the applicant’s specification in at least ¶ 00106 indicates the report can be a web page, e.g. one long page for printing, a page with collapsible sections etc., or a document, spreadsheet, etc., or a machine-readable report (e.g. JSON/XML));
As can be seen from the passages of the Batra reference, techniques for generating comparison files of bills of material (BOMs) were known in the state of the art and previously performed in the industry to report results in an extensible markup language file indicating differences for internal items, manufacturer parts, and/or file attachments. The prior art also teaches or suggests although XML is described for the report, it will be understood that any language or format may be used.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to modify the combined system and methods of Stone, Jaquez, and Mao to include the extracting and comparing steps for bills of material, as taught by Batra to achieve the claimed invention. As disclosed in the Batra reference, the motivation for the combination would have been to provide the advantage of allowing users to view two multi-level bills of material structures within the report and efficiently determine differences in the bills of materials to see what has changed. (¶ 0002, 0015)
With respect to claims 5 and 15, the combination of Stone, Jaquez, Mao, and Batra disclose the method and system,
wherein the at least one reference information comprises at least one of a make, a model, a serial, a revision, a type, an origin, images, visual images, photos, non-visual images, x-ray images, terahertz images, electromagnetic images, electroscopic image, specifications (See Stone ¶ 0075-0076), datasheets (See Stone ¶ 0075-0076), item literature, shopping reviews, counterfeit databases, item databases (See Stone ¶ 0075-0076), shop listings, social media information, or news media information.
With respect to claims 6 and 16, the combination of Stone, Jaquez, Mao, and Batra disclose the method and system,
wherein preprocessing both of the at least one item information and the at least one reference information comprises performing one or more of Optical Character Recognition (OCR), text extraction, Natural Language Processing (NLP), image processing, computer vision, image object recognition, textual lookups, textual resolving, and textual auto-complete on both of the at least one item information and the at least one reference information or validating the accuracy of the at least one item information and the at least one reference information. (¶ 0029, 0037, 0050: Stone discloses prior to artificial neural network (ANN) utilization, an image captured can be pre-processed to remove artifacts and background features that might otherwise complicate and increase the computational power required for the next steps in the analysis…once the excess features are removed, the system 100 can attempt to measure features and look for non-conformities based on a comparative analysis with known good and bad images stored in a database.)
With respect to claims 7 and 17, the combination of Stone, Jaquez, Mao, and Batra disclose the method and system, wherein comparing the at least one item information and the at least one reference information comprises determining: confidence in identification, source, specification (¶ 0113: Stone discloses the confidence level can identify how confident the analysis system is in its determination.); risk, trust and compliance levels (¶ 0037: Stone discloses the analysis system can determine the compliance of the part or assembly.); whether a bill of materials of the physical item is as expected (¶ 0031-0032: Stone discloses the analysis system can automatically inspect and compare workmanship and industry standards to help identify counterfeit components via Institute of Printed Circuits or Military and commercial specifications…automatically compare historical and database data of the supplier, vendor, or manufacturer.); whether an image of the physical item matches with the at least one reference information (¶ 0055: Stone discloses detecting non-conforming electronic component with or without reference to a “golden” reference.); known issues with the physical item (¶ 0064-0065 - Stone); known issues with the bill of materials of the physical item (¶ 0064-0065 - Stone)
With respect to claims 8 and 18, the combination of Stone, Jaquez, Mao, and Batra disclose the method and system,
wherein comparing the at least one item information and the at least one reference information comprises performing automated (¶ 0021, 0037-0032: Stone discloses the analysis system can perform the following tasks at each inspection including automatically identify a part, retrieve technical data reference needed for comparison of the part, inspect and compare with Institute of Printed Circuits, Military, and commercial specification, compare historical and data of the supplier, vendor, or manufacturer.) and manual analysis on the at least one item information and the at least one reference information. (¶ 0034, 0053: Stone discloses the analysis system can provide an aid for human inspectors…including automated instructions for human to reference as to what to inspect.)
With respect to claims 9 and 19, the combination of Stone, Jaquez, Mao, and Batra disclose the method and system,
wherein generating an output data with the at least one result comprises performing one or more of user interface output, report, dashboard, alarm, and notification (Fig. 11, ¶ 0035, 0053, 0089, 0092, 0111, 0123, 0126, 0129, 0136: Stone discloses the analysis system 110 provides a summary report. An example reports 1100 contains analysis results for multiple electronic components. The report summarizes the results for easy review. The report provides baseline and areas of improvement even without reference to a known good component.).
With respect to claims 10 and 20, the combination of Stone, Jaquez, Mao, and Batra disclose the method and system,
wherein storing an output data with the at least one result comprises storing the output data to a local memory or storage (¶ 0065, 0125, 0136: Stone discloses reports could be generated and analysis results could be uploaded to a database 306.), or
transmitting output data to a remote location and storing the output data to a memory at the remote location. (¶ 0065, 0125, 0136: Stone discloses analysis results could be uploaded to other location for storage and later use.)
With respect to claims 21 and 23, the combination of Stone, Jaquez, Mao, and Batra disclose the method and system,
wherein the reputation score of the online source is determined based on a reliability of the online source. (¶ 0042-0043: Jaquez discloses a source with a higher trust score may be considered to provide more accurate data.)
10. Claim(s) 22 and 24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Stone, Jaquez, Mao, Batra in further view of PalChaudhuri (US 2016/0127475 A1).
With respect to claims 22 and 24, the combination of Stone, Jaquez, Mao, and Batra disclose the method and system,
The combination of Stone, Jaquez, Mao, and Batra do not explicitly disclose the following limitations. However, PalChaudhuri discloses a classification engine that determines a reputation value for a website (¶ 0058, 0060) and teaches:
wherein the reliability of the online source is high if the online source is a website of a manufacture of the physical item (¶ 0060: discloses the classification engine generates classification for a first website associated with a high reputation.), medium if the online source is a crowdsourced website (¶ 0060: discloses the classification engine generates classification for a third website associated with a medium reputation value), and low if the online source is an unknown website. (¶ 0060: discloses the classification engine generates classification for a second website associated with a low reputation value.)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to modify the combined system and methods of Stone, Jaquez, Mao, and Batra to include the classification procedures, as taught by PalChaudhuri to achieve the claimed invention. As disclosed in the PalChaudhuri reference, the motivation for the combination would have been to provide advantages for dynamically determining and classifying the category that each website belongs. (¶ 0060, 0062)
Response to Arguments
Applicant's arguments filed 01/02/2026 have been fully considered but they are not persuasive.
With Respect to Rejections Under 35 USC 101
Applicant argues “First, in the analysis under Step 2A prong one, the Examiner states that the claims are directed to the certain methods of human activity because "the step of 'loading' in the context of the claim covers a user providing an image of the physical item for defect detection. Applicant respectfully disagree. MPEP 2106.04(a)(2)(II) clearly discusses that no all methos are abstract idea. The term "certain" qualifies the "certain methods of organizing human activity" grouping as a reminder of several important points. First, not all methods of organizing human activity are abstract ideas (e.g., "a defined set of steps for combining particular ingredients to create a drug formulation" is not a certain "method of organizing human activity"), In re Marco Guldenaar Holding B.V., 911 F.3d 1157, 1160-61, 129 USPQ2d 1008, 1011 (Fed. Cir. 2018).
Applicant respectfully submits that a step such as "receiving a user input" is very commonly recited in the claims in computer software applications. Clearly, allowing a user to "load an image" does not fall within fundamental economic principles or practices, commercial or legal interactions, or managing personal behavior or relationships or interactions between people enumerated in the "certain methods of
organizing human activity" grouping.” The Examiner Respectfully disagrees.
Contrary to the remarks, the claimed invention remains ineligible under Prong One of the two-part analysis. The fact that the claim may involve the use of computer software, does not preclude the limitations from being in the certain methods of organizing human activity grouping. For example, under the broadest reasonable interpretation the Examiner asserts the step for receiving user input is a claim for managing personal behavior or interactions because the limitation involves a person providing an image to the system before conducting a search. With that being said, the reply does not alter the analysis or make the claimed invention any less abstract. For these reasons, the rejections under 101 are being maintained.
Applicant further argues “Second, the Examiner states that the claimed limitations recite a fundamental economic practice performed in supply chain monitoring that is used to protect business against various risks and to identify deviations from expect product characteristics because by analyzing product images, business can verify quality, identify manufacturing defects, inconsistencies in appearances or damage that might otherwise go unnoticed during manual inspection.”
“Applicant agrees that inspections generally help a manufactures economic practice and prevent a commercial risk as it can ensure that a product meets a certain standard for manufacturing, for example. However, inspection is not a part of the fundamental economic practices or principles, which includes hedging, insurance, mitigating risk. To show that, there are following patents that are issued after 2014 and related to product inspection using image comparison: " US Patent 10,664,966 (issued May 26, 2020): Titled "Anomaly detection using image-based physical characterization," this patent describes systems and methods that use image analysis to detect anomalies or defects in a product. " US Patent 10,753,882 (issued August 25, 2020): Titled "Inspection and cosmetic grading through image processing system and method," this patent details a system using a deep learning algorithm trained on a large number of images to efficiently locate, identify, and classify defects by type and dimension.
" US Patent 11,270,430 (issued March 8, 2022): Titled "Wafer inspection using difference images," this patent describes methods for detecting defects in semiconductor wafers by comparing images, addressing issues of false
positives caused by normal process variations. " US Patent 11,361,423 B2 (issued June 14, 2022): Titled: "Artificial intelligence-based process and system for visual inspection", this patent describes applications such as infrastructure monitoring, where an image analyzer compares live images or video feeds with stored reference images
to detect defects. " US Patent 12,130,240 (issued October 29, 2024): Titled: "Inspection method and apparatus for inspecting containers," this patent describes recording an image of a container and comparing it with a reference image formed from numerous previously recorded images to determine if the inspection device is
operational or if a defect is present.”
“It is clear that the USPTO has allowed a number of patents related to inspection using image analysis to issue. The Examiner's consideration of inspection as a reason to classify the claims as "fundamental economic principles or practices" appears inconsistent with the standards set fourth by the USPTO and is therefore unreasonable.
Moreover, Applicant respectfully asserts that the determination of the abstract idea under Step 2A Prong One is based on whether the claim recites the judicial exception, that is, whether a law of nature, natural phenomenon, or abstract idea is set forth or described in the claim. As noted by the Examiner, the specification of the present application explains that detecting anomalies would protect against product
defects, which could be a risk. However, the claims do not explicitly recite preventing a risk. As discussed previously by Applicant, the claims simply recite detecting anomalies based on image analysis.” The Examiner respectfully disagrees.
Contrary to the remarks, the claimed invention remains ineligible under Prong One of the two-part analysis. The Examiner asserts the limitations that recite the abstract idea were properly identified and the previous rejection clearly explained why the limitations fall with the certain methods of organizing human activity grouping. It is also important for applicant to note that abstract ideas may be described at different levels of abstraction.
Accordingly, while it would be acceptable for applicants to cite prior art examples in support of an argument for finding eligibility in an appropriate factual situation, applicants should not be required to model their claims or responses after the prior examples to attain eligibility. The evaluation of whether the claimed invention qualifies as patent-eligible subject matter should be made on a claim-by-claim basis, because claims do not automatically rise or fall with similar claims in an application. With that said, the remarks do not even discuss how the claims parallel the factual patterns discussed in these cited prior art applications, thus the cited applications cannot be used to confer eligibility. For these reasons, the rejections under 101 are being maintained.
Applicant further argues “Third, the Examiner asserts that the claims recite a commercial interaction (i.e., legal obligations, sales/marketing activities, business relations). However, the Examiner fails to specifically identify which feature(s) is considered as reciting the commercial interaction. The Examiner is respectfully reminded that the abstract idea must be recited in the claims in order to determine that the claims are directed to the judicial exception. The claims do not recite any of legal obligations, sales/marketing activities, business relations, although the present application is directed to detecting anomalies.” The Examiner respectfully disagrees.
Contrary to the remarks, the claimed invention remains ineligible under Prong One of the two part analysis. In the instant case, limitations of “loading”, “performing”, “determining”, “forming”, “extracting”, “comparing”, “generating” and “storing” carry out tasks that involve analyzing product images of physical products that users such as manufacturers normally perform to verify quality, identify manufacturing defects, inconsistencies in appearance, or damage that might otherwise go unnoticed during manual inspection. These methods are commercial interactions or processes that take place during quality control and defect detection and may be reasonably characterized as subject matter that falls within the certain methods of organizing human activity grouping. For these reasons, the rejections under 101 are being maintained.
Applicant further argues “Lastly, the Examiner asserts that the claims are directed to mental processes that may be performed in the human mind or by pen/paper. Applicant respectfully disagrees. MPEP 2106.04(a)(2)(ll)(A) states that claims do not recite a mental process when they do not contain limitations that can practically be performed in the human mind. Claim 1 recites, inter alia, sending a signal to an online source over the Internet to retrieve an image of a possible golden item. Claim 11 recites features similar to claim 1. Since the human mind cannot send an electronic signal to an online source over the Internet, the limitations of claims 1 and 11 cannot be practically performed in the human mind. Therefore, claims 1 and 11, as well as their dependent claims, do not recite mental processes. At least for these reasons, Applicant respectfully submit that the claims are not directed to an abstract idea. Thus, the claims are patent eligible.” The Examiner respectfully disagrees.
Contrary to the remarks, the claimed invention remains ineligible under Prong One of the two-part analysis. Here, the applicant does not address any of the limitations that were previously considered in the last Office Action that recited a mental process. Although one may argue that the human mind is unable to process and recognize the electronic stream of data that is being received, transmitted, stored, and etc. by the processor, the Examiner asserts that this is insufficient to confer eligibility. The claims in Alice Corp v CLS Bank also required a computer that processed streams of data, but nonetheless were found to be abstract. Instead, the remarks mainly rely upon the step of “sending a signal to an online source over the internet” which was a limitation addressed under Prong Two – See MPEP 2106.05(g) and is merely performing the necessary data gathering and/or transmitting to aid in performing the abstract idea. For these reasons, the rejections under 101 are being maintained.
Applicant further argues “With regard to the analysis under Step 2A Prong Two, as discussed previously, conventionally, anomalies in a physical item, such as a printed circuit board, are detected by comparing the physical item with a golden reference item. However, the conventional technology does provide an efficient way to detect anomalies when there is no golden reference item of the physical item. To provide a solution, the present invention performs an image-based Internet search based on an image of the physical item, forming text bounds in the physical item in the text bounds, and combining a first one of the text bounds and a second one of the text bounds if the first one of the text bounds is overlapping or within a predetermined proximity of the second one of the text bounds based on the positioning of the detected image features, extracting text information on the image of the physical item to form a first bill of material and extracting text information on the possible golden reference item to form a second bill of materials, comparing the first bill of materials and the second bill of materials to determine if the first bill of materials for the physical item corresponds to the second bill of materials for the possible golden reference item, and if so, and if the source of the possible golden reference item is reliable, then the system determines that the physical item is as expected. If not, the system determines that the physical item contains anomalies.” The Examiner respectfully disagrees.
Contrary to the remarks, the claimed invention remains ineligible under Prong Two of the two-part analysis. The remarks simply restate the combination of limitations as claimed and purport the claim provides an efficient way to detect anomalies. The reply does not discuss any improvements to technology from the Specification regarding the steps being performed nor does it address a technical solution to a technical problem. See MPEP 2106.05(a) The applicant’s remarks do not discuss anything inventive in regards to the ordered combination of elements. At best, the recited steps in the claim are being carried out by “a processor” which is described in at a high-level of generality in light of the Specification, [i.e., ¶ 0042]. The cited passage from the Specification confirms “the processor” recited in the claim(s) is nothing more than a generic computing device that operates in its ordinary or normal capacity to aid in performing the abstract idea. See MPEP 2106.05(f) In this case, relying on [a computer or processor] to perform routine tasks more quickly or more accurately is insufficient to render a claim patent eligible. For these reasons, the rejections under 101 are being maintained.
Applicant further agues “In the Office Action, the Examiner determines that the abstract idea has not been integrated into practical application because the additional elements are not indicative of integration into practical application. However, MPEP 2106.05(a) clearly states that the claim as a whole must to considered to determine whether the judicial exception has been integrated into practical application. It is important to note, the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements. See the discussion of Diamond v. Diehr, 450 U.S. 175, 187 and 191-92, 209 USPQ 1, 10 (1981)) in subsection II, below. In addition, the improvement can be provided by the additional element(s) in combination with the recited judicial exception. See MPEP § 2106.04(d) (discussing Finjan, Inc. v. Blue Coat Sys., Inc., 879 F.3d 1299, 1303-04, 125 USPQ2d 1282, 1285-87 (Fed. Cir. 2018)). Thus, it is important for examiners to analyze the claim as a whole when determining whether the claim provides an improvement to the functioning of computers or an improvement to other technology or technical field. (Emphasis added.)” The Examiner respectfully disagrees.
Contrary to the remarks, the claimed invention remains ineligible under Prong Two to the two-part analysis. Here, the reply does not indicate any of how the additional elements recited in the claim provide an technological improvement. The cited court decisions in Diehr and Finjan discussed specific technological improvements, whereas the presently recited claims do not recite comparable technological improvements. Instead, the claims involve implementing an abstract for detecting anomalies from product images using a generic computing component such as a processor. Also, the claimed methods are not rendered patent eligible by the fact that (using existing machine learning technology – i.e., image object/text recognition and/or classification by executing a machine-learning based computer vision algorithm, wherein the machine- leaning based computer vision algorithm) they perform a task previously undertaken by humans with greater speed and efficiency than could previously be achieved. The response does not explain how these ordered combination of additional elements integrates the judicial exception into a practical application or provide an inventive concept. For these reasons, the rejections under 101 are being maintained.
Applicant further argues “Applicant respectfully submits that claims 1 and 11 recites features in a manner detail enough to achieve the above-discussed object of the present application. Furthermore, as discussed in more details below, none of the applied references, alone or in combination, explicitly or implicitly teach or suggest the claimed invention. Therefore, the claimed invention are not well-known or conventional. Thus, Applicant respectfully submits that the claimed feature amount to significantly more than an abstract idea. In view of the foregoing amendments and remarks, it is respectfully submitted that all claims are directed to statutory subject matter. Reconsideration and withdrawal of the 35 USC 101 rejection are respectfully requested.” The Examiner respectfully disagrees.
Contrary to the remarks, the claimed invention remains ineligible under Prong Two to the two-part analysis. The specificity of the presently recited techniques in claims 1 and 11 does not lead towards eligibility. Even attempting to accept Applicant's view that these particular uses are not well-known, routine, or conventional, the Examiner asserts the courts have previously held "a claim for a new abstract idea is still an abstract idea." SAP, 898 F.3d at 1163 The focus of the claims is not on ... any improvement in computers as tools, but on certain independently abstract ideas that use a computer or processor as tool to implement the abstract idea. For these reasons, the rejections under 101 are being maintained.
With Respect to Rejections Under 35 USC 103
Applicant argues “With regard to Jaquez, its system is focused on identifying a product after receiving a product identifier and resolving conflicting product data from multiple sources. Jaquez explains that after "PDIS 104 has received the entered product identifier, PDIS 104 may access product data corresponding to the product identifier"([0039]), where "Product data 202 may include, for example, product-identifier data 204, image data 206, title data 208, attribute data 210, etc." ([0023]). Jaquez describes comparing this data to identify "agreements and/or disagreements" ([0040]), and specifically states that "in regard to determining image data agreements and/or
disagreements, in one example embodiment, PDIS 104 may employ computer vision technology to analyze and compare received images" ([0041]). Jaquez does not explain how this computer vision is performed and does not describe detecting or positioning image features, forming bounding boxes or text bounds, extracting text from images, tracing parts, or producing structured information from images. The image comparison in Jaquez is used only as part of generating "an identification score" so that "the product may be considered to be identified" ([0045]), and Jaquez does not disclose or suggest forming bills of materials from images, comparing bills of materials between a device under test and a golden unit, or using a trust or reputation score to determine whether a physical item is as expected or anomalous, as required by Claim 1.” The Examiner respectfully disagrees.
In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986). In the instant case, the Jaquez reference teaches [using computer vision to analyze images and determining a reputation score of the online source, i.e., ¶ 0019, 0029, 0032, 0034 0041 – non-final, pgs. 14-15] The previous rejection of record did not cite or rely upon the Jaquez reference for features (such as forming bounding boxes or text bounds, extracting text from images, tracing parts, or producing structured information from images) as disputed by Applicant. The features being argued by Applicant here are taught and/or suggested by the findings provided from the combination of previously references. For these reasons, the rejections under 103 are being maintained.
Applicant further argues “In Mao, the system is directed to detecting counterfeit products on e-commerce platforms by identifying a product's brand or logo from an image or video and comparing that identification to a stored identification corresponding to the product. Mao explains that the system "process[es] the copy of the media file using a deep learning module to obtain an identification of the product" and then "validate[s] the product by comparing the identification of the product with a stored identification corresponding to the product"([0007], [0024]). The deep learning module is described in detail as including "a plurality of convolution layers" that generate multi-scale feature maps, a detection module that produces "intermediate identifications of the product," and a non-maximum suppression module that outputs a final identification ( [0013], [0029], [0043]). Mao further explains that the extracted features include "at least one bounding box location, and at least one logo label corresponding to the at least one bounding box" ( [0017],[0033]), and that the "identification of the product comprises a brand name or a logo image of the product" ([0022]). Mao's use of bounding boxes and deep learning is thus limited to detecting logos or brand identifiers in media files in order to determine whether a listed product is counterfeit. Mao does not disclose or suggest extracting textual information from physical components, forming bills of materials, comparing bills of materials between a device under test and a golden unit, performing Internet image searches, or using reputation scores of online sources to determine whether a physical item is as expected or anomalous, as required by Claim 1.” The Examiner respectfully disagrees.
In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986). In the instant case, the Mao reference teaches [forming, tracing, and combining text bounds, i.e., ¶ 0003-0005, 0073, 0088, 0090-0091 – non-final, pgs. 16-17] The previous rejection of record did not cite or rely upon the Mao reference for features (such as extracting textual information, forming bills of materials, comparing bills of materials between a device under test and a golden unit, performing Internet image searches, or using reputation scores of online sources to determine whether a physical item is as expected or anomalous) as disputed by Applicant. The features being argued by Applicant here are taught and/or suggested by the findings provided from the combination of previously references. For these reasons, the rejections under 103 are being maintained.
Applicant further argues “Batra's disclosure is limited to comparing two existing multi-level bills of material as structured data, not to generating a bill of material from images or physical items. Batra explains that "A bill of material (BOM) is a list of items needed to manufacture an end item" ([0002]) and that the method receives "a first multilevel bill of material and a second multilevel bill of material" for comparison ([0003]-[0004]). The comparison operates by matching "internal items" and then comparing "associations, such as manufacturer parts and/or file attachments" for matched internal items ( [0015], [0020], [0022]). Batra repeatedly emphasizes that the BOMs are retrieved from storage and compared as hierarchical data structures, stating that "the bill of material may then be stored in a relational database" ([0019]) and that comparison processor 104 "receives bills of material for comparison" and compares rows based on configured attributes such as item number or manufacturer part number ([0021], [0037]-1[0040]). Batra does not disclose loading or analyzing images of physical items, performing computer vision, detecting or positioning image features, forming text bounds, extracting text from images, or forming a bill of materials from visual information. Instead, Batra assumes that both the first and second bills of material already exist in structured form and focuses solely on reporting differences between those existing BOMs, which is fundamentally different from the image-based extraction and comparison of bills of materials derived from physical items and online reference images as recited in Claim 1.” The Examiner respectfully disagrees.
In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986). In the instant case, the Batra reference teaches [extracting textual information and comparing first and second bill of materials, i.e., ¶ 0018-0023, 0053, 0056-0058 – non-final, pgs. 17-19] The previous rejection of record did not cite or rely upon the Batra reference for features (such as loading or analyzing images of physical items, performing computer vision, detecting or positioning image features,) as disputed by Applicant. The features being argued by Applicant here are taught and/or suggested by the findings provided from the combination of previously references. For these reasons, the rejections under 103 are being maintained.
Applicant further argues “Stone is directed to automated inspection and counterfeit detection of electronic components, not to extracting a bill of materials or comparing BOMs derived from images of physical items. Stone states that it provides "an automated model-based inspection system for screening electronic components" to "detect counterfeit articles"([0001], [0004]). The system "obtains data associated with an electronic component" and conducts a "multi-tier inspection process to verify a conformance of the electronic component," where each tier includes different identification tests and may produce "fuzzy outputs" ([0005]). Stone explains that the imaging system "can capture images and extract application-specific information from the captured images" ( [0025]) and that the analysis system performs tasks such as "automatically identify a part or assembly" and "automatically perform optical inspection and comparison of dimensions and required portions of the part or assembly" ([0028]-1[0030]). The analysis focuses on detecting non-conformities such as counterfeit markings, dimensional deviations, resurfacing, or incorrect component features ([0047], [0052]). While Stone may compare captured images to "known good and bad images stored in a database"([0037]) or to "reference components or inspection criteria" ([0055]) derived from reference components ( [0055]), Stone does not disclose or suggest forming text bounds around detected image features, extracting textual component identifiers from images, generating a bill of materials from image-based text extraction, or comparing a first and second bill of materials as claimed. Instead, Stone's outputs are inspection determinations such as "pass/fail/inconclusive" results regarding component authenticity or conformance ( [0111], [0089]), not a structured BOM comparison between a physical item and a possible golden item image.” The Examiner respectfully disagrees.
In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986). In the instant case, the previous rejection of record did not cite or rely upon the Stone reference for features (such as forming text bounds around detected image features, extracting textual component identifiers from images, generating a bill of materials from image-based text extraction, or comparing a first and second bill of materials) as disputed by Applicant. As for the output data argument, the passages [¶ 0089, 0111, 0123, 0126, 0129, 0136] from Stone teach or suggest the output data is based on a comparison of the component’s characteristics or one or more reference parts or a comparison of the components characteristics to dimensions or tolerances of the manufacturer which meets the limitation as claimed. The features being argued by Applicant here are taught and/or suggested by the findings provided from the combination of previously references. For these reasons, the rejections under 103 are being maintained.
Applicant further argues “In summary, Stone, Jaquez, Mao and Batra, alone or in combination, fail to teach or suggest image-derived bill of materials generation, comparison of bills of materials extracted from images, Internet image-based discovery of a golden unit, or using online source reputation to gate anomaly determinations. More specifically: " No cited reference teaches image-derived bill of materials generation. Jaquez uses images only to support product identification scoring; Mao detects logos/brands; Stone performs inspection and conformance analysis; Batra assumes pre-existing structured BOMs. None of them disclose detecting components in images, forming text bounds, extracting text, and assembling a BOM from visual data as required by Claim 1.” The Examiner respectfully disagrees.
In the instant case, applicant's arguments fail to comply with 37 CFR 1.111(b) because they amount to a general allegation that the claims define a patentable invention without specifically pointing out how the language of the claims patentably distinguishes them from the references. Here, the arguments discuss features not claimed [such as image-derived bill of materials generation] At best this indicates a field of use for the claimed invention, but this alone is not distinguishable feature in view of the previously cited prior art. The rejection of record clearly explains why the combination of Stone, Mao, Batra references fairly teach or suggest the features of the invention as claimed. For these reasons, the rejections under 103 are being maintained.
Applicant further argues “No reference teaches comparing two image-derived BOMs.
Claim 1 requires forming a first BOM from a physical item image and a second BOM from a reference image, then comparing the two. Batra compares BOMs only when both already exist as structured data; Stone compares measured characteristics, not BOM entries; Jaquez and Mao do not generate BOMs at all.” The Examiner respectfully disagrees.
In the instant case, applicant's arguments fail to comply with 37 CFR 1.111(b) because they amount to a general allegation that the claims define a patentable invention without specifically pointing out how the language of the claims patentably distinguishes them from the references. The Examiner contends the Batra reference teaches or suggests [Fig. 7, ¶ 0018-0023, 0053, 0056-0058: the comparison files are compared and the results are used to generate a report. A user may view the report and quickly determine differences between BOM #1 and BOM #2. The side-by-side comparison allows determinations to be made quickly and easily] As best understood from the passages of Batra, techniques for comparing images of BOM’s were known in the state of the art and previously practiced in the industry. Thus, the teachings from the Batra reference meet the limitations as claimed. For these reasons, the rejections under 101 are being maintained.
Applicant further argues “No reference teaches obtaining a possible golden item via Internet image search. Claim 1 expressly requires performing an Internet search using the image to obtain a possible golden item image from an online source. None of the cited references disclose image-based Internet discovery of a golden unit.” The Examiner respectfully disagrees.
In the instant case, applicant's arguments fail to comply with 37 CFR 1.111(b) because they amount to a general allegation that the claims define a patentable invention without specifically pointing out how the language of the claims patentably distinguishes them from the references.
.
Applicant further argues “The proposed combination of the references relies on impermissible hindsight. Arriving at Claim 1 would require selectively extracting unrelated features from multiple references and re-purposing them to create an image-based BOM extraction, Internet-derived golden reference, and reputation-weighted anomaly determination framework that none of the references teach or suggest. Therefore, the Examiner must be relying on impermissible hindsight knowledge gained from the Applicant's disclosure. This is improper.” The Examiner respectfully disagrees.
The Examiner maintains in response to applicant's argument that the examiner's conclusion of obviousness is based upon improper hindsight reasoning, it must be recognized that any judgment on obviousness is in a sense necessarily a reconstruction based upon hindsight reasoning. But so long as it takes into account only knowledge which was within the level of ordinary skill at the time the claimed invention was made, and does not include knowledge gleaned only from the applicant's disclosure, such a reconstruction is proper. See In re McLaughlin, 443 F.2d 1392, 170 USPQ 209 (CCPA 1971). The cited references of Stone, Jaquez, Mao, and Batra are either in the same field of endeavor as the claimed invention and perform techniques pertinent to the problem faced by the inventor. The cited references provide available knowledge within the level of ordinary skill in the art and do not include knowledge gleaned only from applicant’s disclosure. Therefore, the hindsight arguments are unpersuasive and the rejections under 103 are being maintained.
Applicant further argues “At least for these reasons, Applicant respectfully submits that claim 1 is patentably distinct from Stone, Jaquez, Mao and Batra. Independent claim 11 recite features similar to those of claim 1 and is therefore also patentably distinct from Stone, Jaquez, Mao and Batra. Dependent claims 5-10 and 15-20 are patentable at least for their dependence on claims 1 and 11, respectively, as well as for the additional features they recite.” The Examiner respectfully disagrees.
In the instant case, the claims in independent 11 are substantially similar to the claims recited in claim 1, thus they are being held rejected under the same grounds. As for applicant's arguments directed towards dependent claims 5-10 and 15-20 fail comply with 37 CFR 1.111(b) because they amount to a general allegation that the claims define a patentable invention without specifically pointing out how the language of the claims patentably distinguishes them from the references. For these reasons, the rejections under 103 are being maintained.
Applicant further argues “Moreover, PalChaudhuri is directed to network-level classification of application sessions and webpages, not to analyzing images or physical items. PalChaudhuri explains that the system classifies "an application session for forwarding or refraining from forwarding" data packets based on classification information associated with a request ([0012]), where a network device receives a client request, obtains classification information, and then "based on the classification information, forwarding or refraining from forwarding the first response to the client device" ( [0012],[0069]- [0070]). The classification engine "generates the classification information corresponding to the web address" ([0054]) and in some embodiments determines that information "based on reputation of the website associated with the web address," where reputation is "represented by a value within a predetermined range" ( [0056]). The disclosure repeatedly emphasizes that classification operates on web addresses, webpages, application sessions, and network traffic, for example classifying whether "a response from the web address will be allowed or denied" ( [0055]) or whether a client is redirected to a different webpage ( [0013], [0074]). PalChaudhuri does not disclose loading or analyzing images, performing computer vision, detecting or positioning image features, extracting text from images, forming text bounds, generating
a bill of materials, or comparing bills of materials between a physical item and a golden
reference image. Instead, PalChaudhuri's "reputation" concept is explicitly tied to websites and URLs for network access control ([0056]-[0061]) and is used solely to determine whether network responses are forwarded, throttled, denied, or redirected, which is unrelated to Claim 1's image-based BOM extraction and physical anomaly determination. PalChaudhuri's reputation scoring is limited to website/network traffic control and is not applied to physical item validation or image-based BOM comparison. The remaining references do not use reputation scores at all. Therefore, even if PalChaudhuri is combined with Stone, Jaquez, Mao and Batra, the references do not teach or suggest each and every feature of claims 1 and 11, and their dependent claims. In view of the foregoing amendments and remarks, reconsideration and withdrawal of the rejection under 35 USC 103 are respectfully requested.” The Examiner respectfully disagrees.
In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986). In the instant case, the previous rejection of record did not cite or rely upon the Stone reference for features (such as loading or analyzing images, performing computer vision, detecting or positioning image features, extracting text from images, forming text bounds, generating a bill of materials, or comparing bills of materials between a physical item and a golden reference image) as disputed by Applicant. The features being argued by Applicant here are taught and/or suggested by the findings provided from the combination of previously references. As for PalChaudhuri's website reputation scoring, "the prior art’s mere disclosure of more than one alternative does not constitute a teaching away from any of these alternatives because such disclosure does not criticize, discredit, or otherwise discourage the solution claimed…." In re Fulton, 391 F.3d 1195, 1201, 73 USPQ2d 1141, 1146 (Fed. Cir. 2004). Both PalChaudhuri and the claimed invention are concerned with classifying websites based upon their reputation scores, i.e., high, medium, low. Even if it could be argued that PalChaudhuri is not in the same field of endeavor as the claimed invention, PalChaudhuri is analogous art because it is reasonably pertinent to the problem faced by the inventor of the claimed invention. For these reasons, the rejections under 103 are being maintained.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to EHRIN PRATT whose telephone number is (571)270-3184. The examiner can normally be reached 8-5 EST Monday-Friday.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Lynda Jasmin can be reached at 571-272-6782. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/EHRIN L PRATT/Examiner, Art Unit 3629
/LYNDA JASMIN/Supervisory Patent Examiner, Art Unit 3629