DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
Priority for the instant application is recognized to September 30th, 2021 for the purpose of examination herein regarding prior art based on certified documents filed in Japan.
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, 3-5, 7-9, 11-13 and 15-18 are rejected under 35 U.S.C. 101 because the claimed invention discloses an abstract idea without significantly more.
Step 1: Whether a Claim is to a Statutory Category
In the instant case, claims 1, 3-5, 7-8 and 17 recite a non-transitory computer-readable medium that causes a computer to execute a process/ process, claims 8 and 18 recite a method/ process and claims 9, 11-13 and 15-16 recite an apparatus/ machine that are performing a series of functions. Therefore, these claims fall within the four statutory categories of invention of a process and a machine. Step 1 is satisfied.
Step2A – Prong 1: Does the Claim Recite a Judicial Exception
Exemplary claim 1 (and similarly claims 8 and 9) recites the following abstract concepts that are found to include an enumerated “abstract idea”:
A non-transitory computer-readable recording medium having stored therein an information processing program that causes a computer to execute a process comprising:
obtaining image data in which a predetermined area in front of an accounting machine, which is used by a user to register an article and pay bill, is captured;
generating, by inputting the image data into a machine learning model that is trained to identify an article, a shopping basket and a storage for the article, first area information in which a first class indicating the user who purchases the article and an area where the user appears are associated, second area information in which a second class indicating an object including the article and an area where the object appears are associated, and an interaction between the first class and the second class, wherein the machine learning model only identifies the object with which the user interacts;
identifying, an action taken by the user with respect to the article, based on the first area information, the second area information, and the interaction, wherein the action includes a first action where the user takes out an article that is a pre-purchase article from the shopping basket, a second action where the user makes the accounting machine read a barcode of the article, and a third action where the user puts the article that is a post-purchase article into the storage, and the identifying includes counting a first number of first actions, a second number of second actions and a third number of third actions; and
detecting an unfair action by the user, based on the first number, the second number, the third number and a registered count indicating a number of articles registered on the accounting machine, wherein the detecting includes:
obtaining a scanning count from the accounting machine, the scanning count indicating the number of articles registered on the accounting machine:
selecting a largest number among the first number, the second number and the third number as an article count:
comparing the scanning count with the article count; and
detecting the unfair action if the article count is greater than the scanning count, and outputting a warning.
[Emphasis added to show the abstract idea as bolded being executed by unbolded additional elements that do not meaningfully limit the abstract idea]
This medium claim is grouped within the "certain methods of organizing human activity” grouping of abstract ideas in prong one of step 2A of the Alice/Mayo test because the claims involve a series of steps for sales activities of registering an article and paying a bill by analyzing image data of a sales registration process at an accounting machine, which is a process that is encompassed by the abstract idea of commercial and/ or legal interactions. The specification of the instant application only shows use of a trained machine learning model that is disclosed at a high level of generality without showing a clear training process that discloses how said machine learning model is trained. Further, the specification does not disclose a particular type of machine learning model, but rather only use of types of machine learning models, including a human object interaction detection (HOID) model, neural network and deep learning that are disclosed at a high level of generality. See e.g., MPEP 2106.04(a)(2)(II)(B) and July 2024 Subject Matter Eligibility Example 47 claim 2. Accordingly, claim 1 (and similarly claims 8 and 9) are found to recite abstract idea(s).
Step2A – Prong 2: Does the Claim Recite Additional Elements that Integrate the Judicial Exception into a Practical Application
This judicial exception is not integrated into a practical application because, when analyzed under prong two of step 2A of the Alice/Mayo test, the additional elements of the claims such as non-transitory computer-readable recording medium, computer, machine learning model and accounting machine merely use a computer as a tool to perform an abstract idea and/or generally link the use of a judicial exception to a particular technological environment. Specifically, the non-transitory computer-readable recording medium, computer, machine learning model and accounting machine perform the steps or functions of sales activities of registering an article and paying a bill. The use of a processor/computer as a tool to implement the abstract idea and/or generally linking the use of the abstract idea to a particular technological environment does not integrate the abstract idea into a practical application because it requires no more than a computer (or technical elements disclosed at a high level of generality such as non-transitory computer-readable recording medium, computer, machine learning model and accounting machine) performing functions of obtaining, generating, identifying, detecting, selecting and comparing that correspond to acts required to carry out the abstract idea (MPEP 2106.05(f) and (h)). Accordingly, the additional elements do not impose any meaningful limits on practicing the abstract idea, and the claims are directed to an abstract idea.
Step2B: Does the Claim Amount to Significantly More
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when analyzed under step 2B of the Alice/Mayo test, the additional elements of non-transitory computer-readable recording medium, computer, machine learning model and accounting machine being used to perform the steps of obtaining, generating, identifying, detecting, selecting and comparing amounts to no more than using a computer or processor to automate and/or implement the abstract idea of sales activities of registering an article and paying a bill. As discussed above, taking the claim elements separately, non-transitory computer-readable recording medium, computer, machine learning model and accounting machine perform the steps or functions of commercial and/or legal interactions of sales activities of registering an article and paying a bill. These functions correspond to the actions required to perform the abstract idea. Viewed as a whole, the combination of elements recited in the claims merely recite the concept of commercial and/or legal interactions of sales activities of registering an article and paying a bill because said combination of elements remains disclosed at a high level of generality. Therefore, the use of these additional elements does no more than employ the computer as a tool to automate and/or implement the abstract idea. The use of a computer or processor to merely automate and/or implement the abstract idea cannot provide significantly more than the abstract idea itself (MPEP 2106.05(l)(A)(f) & (h)). Therefore, the claims are not patent eligible.
Independent claims 8 and 9 describe a method and apparatus performing the functions of obtaining, generating, identifying, detecting, selecting and comparing relating to sales activities without additional elements beyond technical elements disclosed at a high level of generality such as a processor, a memory, machine learning model and accounting machine, respectively, that provide significantly more than the abstract idea of commercial and/or legal interactions of sales activities of registering an article and paying a bill as noted above regarding claim 1. Therefore, these independent claims are also not patent eligible.
Dependent claims 3 and 11 further limit their respective independent claims 1 and 9 by adding determining and identifying functions however, these steps remain as performed by technical elements disclosed at a high level of generality and are not significantly more than the abstract idea of commercial and/or legal interactions of sales activities of registering an article and paying a bill. Therefore, dependent claims 3 and 11 are also not patent eligible. Further, the dependency of these claims on ineligible independent claims 1 and 9 also renders dependent claims 3 and 11 as not patent eligible.
Dependent claims 4 and 12 further limit their respective independent claims 1 and 9 by adding identifying, determining and detecting functions however, these steps remain as performed by technical elements disclosed at a high level of generality and are not significantly more than the abstract idea of commercial and/or legal interactions of sales activities of registering an article and paying a bill. Therefore, dependent claims 4 and 12 are also not patent eligible. Further, the dependency of these claims on ineligible independent claims 1 and 9 also renders dependent claims 4 and 12 as not patent eligible.
Dependent claims 5 and 13 further limit their respective independent claims 1 and 9 by adding displaying and notifying functions however, these steps remain as performed by technical elements disclosed at a high level of generality and are not significantly more than the abstract idea of commercial and/or legal interactions of sales activities of registering an article and paying a bill. Therefore, dependent claims 5 and 13 are also not patent eligible. Further, the dependency of these claims on ineligible independent claims 1 and 9 also renders dependent claims 5 and 13 as not patent eligible.
Dependent claims 7 and 15 further add detecting, generating, inputting, identifying and counting that rely on the trained machine learning model of claims 1 and 9 with no further disclosure of said model or how said model is trained. Therefore, these steps remain as performed by technical elements disclosed at a high level of generality and are not significantly more than the abstract idea of commercial and/or legal interactions of sales activities of registering an article and paying a bill. Therefore, dependent claims 7 and 15 are also not patent eligible. Further, the dependency of these claims on ineligible independent claims 1 and 9 also renders dependent claims 7 and 15 as not patent eligible.
Dependent claims 16-18 further add inputting, associating, training and matching and descriptive material to show a training process for the machine learning model of their respective independent claims 1, 8 and 9. However, said process remains as performed by technical elements disclosed at a high level of generality that are merely applying said technical elements without clearly disclosing in a manner that is obvious to one of ordinary skill art how the results of the claimed process are achieved and are not significantly more than the abstract idea of commercial and/or legal interactions of sales activities of registering an article and paying a bill. Therefore, dependent claims 16-18 are also not patent eligible. Further, the dependency of these claims on ineligible independent claims 1, 8 and 9 also renders dependent claims 16-18 as not patent eligible.
Response to Remarks
Applicant's arguments filed 09/12/2025 have been fully considered but they are not persuasive.
Rejection under 35 U.S.C. § 101:
Contrary to the applicant’s assertion that claimed invention of amended independent claim 1 (and similarly amended independent claims 8 and 9) is a technical improvement to the data processing logic of a multi-stage computer vision process, the previous rejection under 35 U.S.C. § 101 is maintained. Claims 1, 8 and 9 remain to merely apply a trained machine learning model to said multi-stage computer vision process without clearly showing how said model is trained. This leaves said claims not eligible for a patent because said claims remain as being executed by technical elements disclosed at a high level of generality such that any improvement shown in the claims is to the abstract idea itself rather than the underlying technology. The claims themselves must clearly show the improvement and the specification of an instant application is not read into the claims during examination.
Rejection under 35 U.S.C. § 103:
The previous rejection of amended claims 1, 3-5, 7-9, 11-13 and 15 under 35 U.S.C. § 103 is withdrawn. The examiner agrees with the applicant in that the combination of Yu and Okamura do not teach the features of amended independent claims 1, 8 and 9 requiring:
wherein the machine learning model only identifies the object with which the user interacts;
identifying, an action taken by the user with respect to the article, based on the first area information, the second area information, and the interaction, wherein the action includes a first action where the user takes out an article that is a pre-purchase article from the shopping basket, a second action where the user makes the accounting machine read a barcode of the article, and a third action where the user puts the article that is a post-purchase article into the storage, and the identifying includes counting a first number of first actions, a second number of second actions and a third number of third actions; and
detecting an unfair action by the user, based on the first number, the second number, the third number and a registered count indicating a number of articles registered on the accounting machine, wherein the detecting includes:
obtaining a scanning count from the accounting machine, the scanning count indicating the number of articles registered on the accounting machine:
selecting a largest number among the first number, the second number and the third number as an article count;
comparing the scanning count with the article count; and
detecting the unfair action if the article count is greater than the scanning count, and outputting a warning.
As noted in the previous rejection, Yu does not teach the claimed three distinct types of monitored user actions. Okamura was relied to teach these three user actions wherein a first number of actions where the user takes out a pre-purchase article from the shopping basket, a second number of actions where the user makes the accounting machine read a barcode, and a third number of actions where the user puts a post-purchase article into storage. However, Yu and Okamura do not teach selecting a largest number among the first number, the second number and the third number as an article count; comparing the scanning count with the article count; and detecting the unfair action if the article count is greater than the scanning count, and outputting a warning. This selection of the largest among the first, second and third numbers representing the claimed first, second and third user actions relating to scanning an item to register an article and pay a bill has not been found to be taught by prior art alone or in an obvious combination. Therefore, independent claims 1, 8 and 9 of the instant application are considered allowable over prior art. Dependent claims 3-5, 7, 11-13, 15 and new claims 16-18 are considered allowable for their dependency on their respective independent base claims 1, 8 and 9.
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 MATTHEW S WERONSKI whose telephone number is (571)272-5802. The examiner can normally be reached M-F 8 am - 5 pm EST.
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/MATTHEW S WERONSKI/Examiner, Art Unit 3627
/MICHAEL JARED WALKER/Primary Examiner, Art Unit 3627