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 .
Status of the Claims
Claims 1, 3, 8, 11, 13, 14, 16, and 17 are amended. Claims 2, 5, 12, and 15 are canceled. Claims 1, 3, 4, 6-11, 13, 14, and 16-20 are pending.
Response to Arguments
Applicant's arguments filed 05/25/2026 regarding 35 U.S.C. 101 have been fully considered but they are not persuasive.
The Claims Recite An Abstract Idea Under Step 2A Prong One
Applicant argues that the claims are not directed to certain methods of organizing human activity nor mental processes. Examiner disagrees.
Step 2A Prong One of the Alice/Mayo framework evaluates whether an abstract idea is set forth or described in the claim. The Federal Circuit has explained that "the 'directed to' inquiry applies a stage-one filter to claims, considered in light of the specification, based on whether 'their character as a whole is directed to excluded subject matter."' Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335 (Fed. Cir. 2016) (quoting Internet Patents Corp. v. Active Network, Inc., 790 F.3d 1343, 1346 (Fed. Cir. 2015)). It asks whether the focus of the claims is on a specific improvement in relevant technology or on a process that itself qualifies as an "abstract idea" for which computers are invoked merely as a tool. Here, it is clear from the Specification (including the claim language) that claim 1 focuses on an abstract idea, and not on an improvement to technology and/or a technical field. Applicant’s specification recites:
[0002] “The present disclosure relates to a method of providing a parking system using QR code based on accurate recognition of a vehicle license plate, more particularly relates to a method of providing the parking system using the QR code including a step of accurately recognizing the license plate through a camera installed to a parking lot in snowy and rainy inclement weather, a step of accurately recognizing the license plate when the vehicle’s license plate is not clearly visible from the side, a step of accurately recognizing the license plate when the vehicle’s license plate is not clearly visible from above or a step of accurately recognizing the license plate when the license plate is mounted on the side of the vehicle and is not properly recognized from the front.”
Further, Specification [0003]-[0009] further recites:
[0004] In general, a parking system with a barrier bar requires vehicles to stop when entering and exiting the parking lot. In the case of exit, additional time is needed for payment, resulting in traffic congestion at the exit.
[0005] Additionally, for off-street parking lots, a parking attendant had to check the entry time each time, and drivers had to pay the attendant when leaving, resulting in additional time being spent.
[0006] When a camera capable of recognizing the vehicle license plate is installed in the parking lot, it may fail to recognize the license plate if rain or snow causes moisture, fogging, or partial obstruction due to snow.
[0007] During inclement weather, occlusion causes recognition accuracy to drop of the license plate, and diagonal positioning also decreases the recognition rate. Furthermore, modern cars often have aerodynamic designs that result in wedge‑shaped front ends, reducing recognition rates. High-performance vehicles sometimes feature large front air intakes to increase engine airflow and improve brake pad cooling, necessitating side-mounted license plates, which can lead to lower recognition rates using conventional methods.
[0008] Accordingly, there is a need for a parking system using QR code that may accurately recognize the license plate even in inclement weather.
[0009] To solve problems of the conventional technique, the present disclosure is to provide a method of accurately recognizing a license plate through a camera installed in a parking lot in inclement weather, accurately recognizing the license plate from the side or above or accurately recognizing the license plate when the license plate is mounted on the side of the vehicle, by using a machine learning.
The cited portions of the specification gives the crux of the claimed invention.
The claims, considered in light of the specification, based on whether their character as a whole is directed to excluded subject matter recites limitations that correspond to certain methods of organizing human activity (managing personal interactions, behavior, relationships; commercial interactions; business relations) as evidenced by limitations detailing receiving and analyzing images of a vehicle entering a parking information, user information corresponding to the user profile and/or phone number and other personal information, and performing payment of a parking fee. The claims also correspond to mental processes (observation, evaluation, judgment, opinion) since the claim limitations also describe the observation and evaluation of parking associated or related data, and making a decision or condition (judgment/opinion) based on the observed and evaluated data. The claims also recite a license plate recognition model and preset machine learning model (interpreted as an algorithm as also indicated in the specification) that amounts to mathematical concepts (mathematical relationships, formulas, equations, or calculations). The claim recites an abstract idea under Step 2A Prong One.
The steps of extracting a polygonal shape corresponding to the license plate, transforming the polygonal shape into a preset rectangular shape, and extracting text information describes the result of a perspective-normalization and character reading processes, not a technical means of achieving it. A human observing an angled photograph of a license plate can visually identify its outline and read the text or numeric characters, which is fundamentally observation, evaluation, judgment, and opinion (mental processes). Utilizing a camera and sever to perform this at a computer speed or scale does not change the character of the underlying concept. Additionally, the MPEP makes it clear that claims can recite mental processes even if they are implemented on a computer (MPEP §2106.04(a)(2)(III)).
Applicant’s argument that a human mind cannot perform these steps because the processes requires a physical sever is unpersuasive. Again, as indicated in MPEP §2106.04(a)(2)(III), claims can recite a mental process even if they are claimed as being performed on a computer. If the claimed invention is described as a concept that is performed in the human mind and applicant is merely claiming that concept performed 1) on a generic computer, or 2) in a computer environment, or 3) is merely using a computer as a tool to perform the concept, the claim is considered to recite a mental process. Applicant’s recitation of the additional element of a server is a computer components recited at a high-level of generality performing the above-mentioned limitations. The combination of the additional element of the server is no more than mere instructions to apply the judicial exception using a generic computer.
Applicant’s argument regarding materially altering pixel data by itself lacks specificity, and is not evidence of a technical improvement. This generic characterization does not establish that the claimed transformation reflects a technical solution to a technical problem. The claim only recites the functional outcome of normalizing a distorted polygonal shape into a rectangle, which itself is also a known generic image perspective correction applied in license plate reading. This is not a claimed technical rule or algorithm. Further, the use of the machine learning model does not support a technical improvement argument and further confirms that the claim is result-oriented. No details of an improvement tin machine learning is presented in the claims nor specification, machine learning is only leveraged in the business process (inputting data, and getting output).
For the reasons set forth above, the claims recite an abstract idea under Step 2A Prong One.
The Judicial Exception Is Not Integrated Into A Practical Application Under Step 2A Prong Two
Applicant argues that the claims integrate the judicial exception into a practical application. Examiner disagrees.
Step 2A Prong Two evaluates whether additional elements, individually or in combination, integrate the judicial exception into a practical application. Applicant’s assertion is anchored to the claim language detailing the observation, evaluation, judgment, opinion (which has already been indicated as corresponding to the judicial exception). The claims themselves does not improve, for example, computer functionality or camera hardware, image sensor operations, sever processing efficiency, memory usage, etc. The claims use existing generic-capture and processing components to perform a conditioning step in service of the judicial exception (recognizing or verifying a license plate for parking access). The courts have identified limitations that did not integrate a judicial exception into a practical application: (see MPEP §2106.04(d))
Merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea;
Adding insignificant extra-solution activity to the judicial exception;
Generally linking the use of a judicial exception to a particular technological environment or field of use;
In the applicant’s claimed invention, the judicial exception is not integrated into a practical application simply because the claims recite the additional elements of: a server, a camera, a QR-code link, preset machine learning model, license plate recognition model, and a user terminal. The additional elements of the server and user terminal are computer components recited at a high-level of generality performing the above-mentioned limitations. The combination of the additional elements are no more than mere instructions to apply the judicial exception using a generic computer. Further, QR-code link, and camera amounts to generally linking the judicial exception to a particular field of use (payment & license plate recognition in vehicle parking) Accordingly, in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea.
The alleged improvement at best is an improvement in the judicial exception itself, not an improvement in computers or technology. The business process is merely implemented on the computer which is an improvement in the business process: accurately recognizing the license plate even in inclement weather. Technical improvement focuses on enhancing the tools, software, or machinery, while business process improvement focuses on streamlining the steps, workflows, and methodologies people use to do their work. Applicant’s claims fall in the latter as evidenced by the specification and claims. It is important to note, that the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements. The improvement can be provided by the additional element(s) in combination with the recited judicial exception (see MPEP §2106.05(a)). As analyzed above, in applicant’s claims the combination of the additional elements are no more than mere instructions to apply the judicial exception using a generic computer, and generally linking the judicial exception to a particular field of use. Accordingly, in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea.
The Claims Do Not Include Additional Elements That Are Sufficient To Amount To Significantly More Than The Judicial Exception Under Step 2B.
Applicant argues that the claims amount to significantly more than the abstract idea. Examiner disagrees.
Applicant argues that their claims are not well-understood, routine, and conventional activity. Applicant is reminded that, under step 2B, whether the additional elements are well-understood, routine, and conventional activity is only one consideration under Step 2B. Limitations that the courts have found not to be enough to qualify as "significantly more" when recited in a claim with a judicial exception also include: (see MPEP §2106.05)
Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer; and
Generally linking the use of the judicial exception to a particular technological environment or field of use;
Thus, since the additional elements amount to no more than mere instructions to apply the exception using a generic computer, and generally linking the judicial exception to a particular field of use, when viewed as an ordered combination, nothing in the claims add significantly more (i.e. an inventive concept) to the abstract idea. Mere instructions to apply an exception using a generic computer cannot provide an inventive concept. Thus, when viewed as an ordered combination, nothing in the claims add significantly more (i.e. an inventive concept) to the abstract idea. The claims are not patent eligible
The 35 U.S.C. 101 rejection is maintained.
Applicant’s arguments, see pg. 16, filed 05/26/2026, with respect to 35 U.S.C. 103 have been fully considered and are persuasive. The 35 U.S.C. 103 rejection has been withdrawn.
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, 4, 6-11, 13, 14, and 16-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e. an abstract idea) without significantly more.
Claims 1, 3, 4, and 6-10 recite a method (i.e. process), and claims 11, 13, 14, and 16-20 recite a server (i.e. machine). Therefore claims 1, 3, 4, 6-11, 13, 14, and 16-20 fall within one of the four statutory categories of invention.
Independent claims 1 and 11 recite the limitations: training a license plate recognition model based on multiple training data including the license plate; receiving an image of a vehicle entering in a parking lot from a [camera] installed to a parking area and extracting text information of the license plate by inputting the received image to the license plate recognition model, wherein extracting the text information includes prior to extracting the text information, extracting a license plate region as a polygonal shape and transforming the polygonal shape into a preset rectangular shape; verifying parking area identification information of a parking area on which the vehicle parks when the [server] receives an image of the parked vehicle; completing entry by associating the parking area identification information, entry time, and recognized license plate with user profile including phone number and payment method received via a [QR-code link], or, when pre-registered, by automatically retrieving the user profile linked to the recognized license plate; and processing an exit of the vehicle related to the user profile and performing payment of parking fee based on the payment method when an exit signal is received from a [user terminal] or a license plate of an exited vehicle in the image received from the [camera] matches with the license plate of the vehicle related to the user profile; wherein the step (a) includes: storing a plurality of training data: extracting an image region corresponding to the license plate in each of the training data: identifying text of the license plate in the extracted image region; generating refined training data by adding defect images to the extracted image region; and training a preset machine learning model by inputting the refined training data and corresponding texts to the preset machine learning model such that the text is outputted when the refined training data is inputted to the preset machine learning model, wherein a vehicle number on the license plate is accurately recognized though a part of the vehicle number is occluded under cases corresponding to the defect images according to training result of the preset machine learning model through the refined training data, one of the cases is a case in snow or rain. The invention and claims are drawn towards a parking system that accurately recognizes license plates and the claim limitation corresponds to certain methods of organizing human activity (managing personal interactions, behavior, relationships; commercial interactions; business relations) as evidenced by limitations detailing receiving and analyzing images of a vehicle entering a parking information, user information corresponding to the user profile and/or phone number and other personal information, and performing payment of a parking fee. The claim also corresponds to mental processes (observation, evaluation, judgment, opinion) since the claim limitations also describe the observation and evaluation of parking associated or related data, and making a decision or condition (judgment/opinion) based on the observed and evaluated data. The claims also recite a license plate recognition model and preset machine learning model (interpreted as an algorithm as also indicated in the specification) that amounts to mathematical concepts (mathematical relationships, formulas, equations, or calculations). The claim recites an abstract idea.
Note: The features or elements in brackets in the above Step 2A Prong One section are inserted for reading clarity, but are analyzed as “additional elements” under Step 2A Prong Two and Step 2B below.
The judicial exception is not integrated into a practical application simply because the claims recite the additional elements of: a server, a camera, a QR-code link, preset machine learning model, license plate recognition model, and a user terminal. The additional elements of the server and user terminal are computer components recited at a high-level of generality performing the above-mentioned limitations. The combination of the additional elements are no more than mere instructions to apply the judicial exception using a generic computer. Further, QR-code link, and camera amounts to generally linking the judicial exception to a particular field of use (payment & license plate recognition in vehicle parking) Accordingly, in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to no more than mere instructions to apply the exception using a generic computer, and generally linking the judicial exception to a particular field of use. Mere instructions to apply an exception using a generic computer cannot provide an inventive concept. Thus, when viewed as an ordered combination, nothing in the claims add significantly more (i.e. an inventive concept) to the abstract idea. The claims are not patent eligible.
Dependent claims 7 and 17 recite the limitations that the generating the refined training data includes: adding multiple Gaussian-blur masks or multiple white occlusion masks to arbitrary local regions within the extracted image region. The limitations are further directed to the judicial exceptions analyzed above. Further, the addition of multiple Gaussian blur masks amounts to mathematical concepts since Gaussian blur applies a mathematical Gaussian function to smooth images, reduce noise, and minimize detail. The claims are not patent eligible.
Dependent claims 3, 4, 6, 8-10, 13, 14, 16, and 18-20 recite additional limitations that are further directed to the abstract idea analyzed in the rejected claims above and/or additional elements that have been analyzed in the rejected claims above. Thus, claims 3, 4, 6, 8-10, 13, 14, 16, and 18-20 are also rejected under 35 U.S.C. 101.
Allowable Subject Matter
Claims 1, 3, 4, 6-11, 13, 14, and 16-20 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 101, set forth in this Office action.
The closest patent or patent application prior art reference found that is relevant to the applicant’s invention includes DeSantola (2022/0292618) and An (2025/0014363). DeSantola discloses a system that trains machine learning models using image data to learn vehicle identification, the image data being received from camera that incudes parking lots. AN discloses a vehicle identity recognition device that includes a machine learner to perform machine learning by inputting the first region of interest as training data; and an image matcher to determine whether the first region of interest on which the machine learning is performed matches the second region of interest. Neither reference, individually nor in combination, appears to disclose the detailed amended limitations of the applicant’s claims pertaining to training the machine learning model. The claims appear to overcome the prior art.
The closest non-patent literature prior art reference found that is relevant to the applicant’s invention includes the publication “Research on License Plate Recognition Algorithms Based on Deep Learning in Complex Environment” which discusses the application of deep learning in license plate recognition, and introducing the most advanced algorithms from the three main technical difficulties: license plate skew, image noise, and license plate blur. The reference does not appear to disclose the detailed amended limitations of the applicant’s claims pertaining to training the machine learning model. The claims appear to overcome the prior art.
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 DIONE N SIMPSON whose telephone number is (571)272-5513. The examiner can normally be reached M-F; 7:30 a.m.-4:30 p.m..
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, Sarah Monfeldt can be reached at (571) 270-1833. 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.
DIONE N. SIMPSON
Primary Examiner
Art Unit 3628
/DIONE N. SIMPSON/ Primary Examiner, Art Unit 3629
Prosecution Insights