Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant’s arguments and amendment have persuasively overcome the drawing objections and the 112(a) rejections. The 102 rejections have been updated to be 103 rejections.
The remaining issues are addressed below.
Double Patenting
Applicant argues:
Claims 1, 6, 11 and 30 are amended in a two-part form to exclude those elements disclosed in US Patent No. 12,062,244 ("the '244 patent")
Examiner responds:
The examiner does not understand this argument.
Applicant argues:
Applicant submits that at least such features are not disclosed or suggested in the '244 patent, such that the '244 patent fails to support a prima facie case of obviousness of claim 18.
Examiner responds:
To the extent that there is a difference between four cameras and a single panoramic camera, such a difference is obvious in view of the applied art and precedent.
(There are no arguments regarding 112b)
The arguments over the 103 rejection argue features that, even if not taught by Horn or Merwaday, are legally obvious.
Information Disclosure Statement
The information disclosure statement filed August 3, 2026 fails to comply with 37 CFR 1.98(a)(2), which requires a legible copy of each cited foreign patent document; each non-patent literature publication or that portion which caused it to be listed; and all other information or that portion which caused it to be listed. It has been placed in the application file, but the information referred to therein has not been considered.
The Japanese Office Action has not been translated. Additionally, many of the references are not translated. MPEP 609.04(a)(III) explains “the explanation required is limited to the relevance as understood by the individual designated in 37 CFR 1.56(c) most knowledgeable about the content of the information at the time the information is submitted to the Office.” Therefore, if someone with a duty under rule 56 can read the foreign document, Applicant may wish to submit a translation.
Specification
The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed.
The following title is suggested: Motorcycle Using Artificial Intelligence for License Plate Recognition.
Appropriate correction is required.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-6, 8, 11, 17-23, 25, and 27-34 (all claims) are rejected on the ground of nonstatutory double patenting as being unpatentable over the claims of US 12062244 B2 in view of the prior art as applied below.
Both the pending claims and the conflicting patent are both directed to “AI motorcycles” that read license plates. Further, any differences between the present claims and the claims in any of the conflicting patents are obvious in view of Horn, Merwaday, and Legal Precedent as applied below. It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the Horn, Merwaday, and Legal Precedent with US 12062244 B2 for implementation details (especially as the patent claims lack implementation details). Based on the findings herein, this is an example of “(A) Combining prior art elements according to known methods to yield predictable results.” MPEP 2143.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-6, 8, 11, 17-23, 25, and 27-34 (all claims) are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Examiner Notes
The claims are replete with drafting errors, such claim 33’s reference to inclination angles in step 3 of claim 11, but claim 11 introduces the inclination angles in step 2 and only references them in step 3. Further, the claims recite a huge number of method steps in system/apparatus claims. In the interest of compact prosecution, the examiner has identified exemplary 112 problems below, but this is not intended to be a complete list of shortcomings.
Many claim elements below are rejected as being new terminology. The examiner has not additionally rejected these claims as lacking written description support because there is a lack of clarity as to what the intended functions are. If Applicant uses known technical terminology (such as reciting that claim 3’s “5G Wifi module” is a “mobile phone”), this is expected to overcome the new terminology rejection and avoid 112a rejections. However, reciting devices, units, or module in terms of what they do raises written description concerns (e.g., reciting a software module configured to perform AI is expected to be rejected).
Claims 1-6, 8, 18-23, 25, and 27-29 recite “AI identification motorcycle,” but this is new terminology. MPEP 2173.05(a).
Claims 11, 17, and 30-34 recite “AI identification vehicle,” but this is new terminology. MPEP 2173.05(a).
Claims 1 and 18 recite various “devices” (such as “AI device” or “image acquisition device”), but each of these are new terminology (with the exception of “display device”). MPEP 2173.05(a).
Additional “devices” (such as claim 2 “current regulation device”) are recited by the dependent claims, and these are likewise rejected.
Claim 1 recites “the power supply management device at least executing a process of,” but this is a method step in an apparatus claim. MPEP 2173.05(p)(II).
Claim 1 recites additional instances of method steps, such as those where “being” is recited. This issue (i.e., “being”) also occurs in various dependent claims, including those that dependent from claim 18.
Claim 1 recites a “reset switch,” but the claim recites its functions as things other than resetting, so it is unclear what weight to give to “reset.”
Claims 1-6, 8, 11, 17-23, 25, and 27-34 recite “its control system” but there are two problems. First, is a lack of antecedent basis. MPEP 2173.05(e). Second, “control system” indefinite because it is unclear if this is the control system for the vehicle, some of the AI (e.g., claim 11’s “a license plate recognition control system”) or any system that controls anything.
Claims 1, 6, 11, and 30 recite “which is characterized,” but the following language is not a characterization, so it is unclear what the relationship is.
Claims 3, 20, 25-27, 29, and 30 recite various “modules,” but each of these are new terminology. MPEP 2173.05(a).
Claim 4 recites “mobile phone image wireless communication mechanism,” but this is new terminology. MPEP 2173.05(a).
Claim 4 recites “the App,” but this lacks sufficient antecedent basis. MPEP 2173.05(e).
Claims 20-23, 25, 27, and 30 recite various “units,” but each of these are new terminology (with the exception of “processing unit”). MPEP 2173.05(a).
Dependent claims are likewise rejected.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The claims recite an unusual level of technical detail that appears unrelated to the field of the invention. The invention is directed to investigating parking and crime using a license plate reader on a vehicle. Specification, [0001]. However, the claims recite features such as button configurations or serial interface standards that are not of technical importance to the field of the invention. Here, such elements are rejected as obvious as a matter of design choice. MPEP 2144.04(VI)(C). Further, because these elements do not impact the inventive thrust (e.g., the RS-232 communication standard is a known substitute for the purpose of communicating, but further specifics beyond that communication occurs are not relevant to the field of the invention), they are also understood as substitutes. MPEP 2144.06(II).
Claims 1-6, 8, 11, 17-23, 25, and 27-34 (all claims) are rejected under 35 U.S.C. 103 as being unpatentable over US20220092327A1 (“Powershow”) in view of legal precedent.
Claims 1-6, 8, 11, 17-23, 25, and 27-34 (all claims) are mapped to Powershow, Fig. 1. Note that the rejection is not limited to what is shown in Powershow, Fig. 1, but includes Powershow’s description of what is shown. MPEP 1207.03(a). For example, Powershow describes first and second plate image acquisition devices that teach claim 8’s “license plate recognition functions of the [first and second] image acquisition devices.”
Present application, Fig. 3 (“an AI motorcycle according to the present invention”)
Powershow, Fig. 1
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Applicant has argued that Powershow does not teach all of the claimed features. Remarks, p. 30. Such features are legally obvious as per the above note.
Claims 1-6, 8, 11, 17-23, 25, and 27-34 (all claims) are rejected under 35 U.S.C. 103 as being unpatentable over US20210225161A1 (“Horn”) in view of US20230300579A1 (“Merwaday”) and legal precedent.
1. An AI identification motorcycle with its control system, including:
a motorcycle (Horn, [0032] “While illustrated as a car, it is contemplated that mobile unit 102 may be any suitable motor vehicle, such as a motorcycle, truck, and bus.”)
an AI device electrically connected to the battery for motorcycle activation, (Horn, abstract, “The imaging device may capture license plate information and other data, such as characteristics corresponding to the driver of the vehicle.” Horn’s capabilities teach the claimed AI.)
a first image acquisition device electrically connected to the AI device, (Horn, Fig. 2A, cameras 204)
a second image acquisition device electrically connected to the AI device, (Horn, Fig. 2A, cameras 204)
a display device electrically connected to the AI device, (Horn, Fig. 3A, display 308)
a heat dissipation device electrically connected to the AI device, and (Horn, Fig. 3A, vents)
a power supply management device electrically connected to the AI device; (Horn, [0037] “For power, imaging device 104 may be operatively connected to a power source of the mobile unit 102.”)
the AI device and the heat dissipation device being provided in an storage compartment of the motorcycle, (Horn, Fig. 3A)
the first image acquisition device and the second image acquisition device being installed on both right and left side of a head of the motorcycle respectively, (Horn, [0041] “As shown in FIG. 2A, cameras 204 may be positioned on side mirrors 208 of mobile unit 202, however, other locations are contemplated.”
the display device being provided over a dashboard on the head of the motorcycle, (Horn, Fig. 3A)
the power supply management device being provided in rear container of the motorcycle; which is characterized: (Horn, Fig. 2A, LPR system 206. Horn’s License Plate Reader is shown in a rear container.)
the power supply management device at least executing a process of turning on the AI device, a process of turning off the AI device, and a procedure of charging the battery for motorcycle activation; (Horn, [0011] “The imaging devices may be configured to continuously monitor surroundings and/or wake from a low power state in response to detecting the vehicle.”)
in executing the process of turning on the AI device, a motorcycle electric switch provided with the battery for motorcycle activation being turned on, and a reset switch of the power supply management device being activated to turn on the battery for motorcycle activation to output power to the AI device, the first image acquisition device, the second image acquisition device, the display device and the heat dissipation device, as well as a boot process and a system screen being displayed on the display device to complete the turning on of the AI device; (Horn, [0031] “In yet another example, imaging device 104 may be configured to activate in response to a user action, such as pressing a button that sends a command to the imaging device 104.”)
in executing the process of turning off the AI device, the motorcycle electric switch being turned off, and the AI device entering a shutdown process, after the display device displaying that the shutdown is complete, the reset switch being activated until no output screen being displayed on the display device, indicating that the shutdown of the AI device is completed; (Horn, [0080] “In one approach, a user input, such as engaging a user interface (e.g., pressing a button), may initiate the process and/or wake one or more components from a powered down state (i.e. sleep mode).”)
in executing the procedure of charging the battery for motorcycle activation, a charging selection switch of the power supply management device being activated to a position of a vehicle charging side, such that the power supply management device receives the electric power of the motorcycle generator of the motorcycle to provide powering for an input terminal of the power supply management device as charging of the battery for motorcycle activation, and supply the power directly or indirectly required for the AI device, the first image acquisition device, the second image acquisition device, the display device and the heat dissipation device to operate; (Horn, [0047] “While illustrated as buttons, it is contemplated input controller 310 may include dials, slider switches, joysticks, click wheels, and the like.” The following paragraph, [0048] specifies that these buttons activate the surveillance system 300.)
in addition, the charging selection switch of the power supply management device can also be activated to a position of an external charging side, such that a bluetooth communication charger of the power supply management device receives AC power from an external power source as the charging of the battery for motorcycle activation, to supply the power directly or indirectly required for the AI device, the first image acquisition device, the second image acquisition device, the display device and the heat dissipation device to operate. (Horn, [0047] “While illustrated as buttons, it is contemplated input controller 310 may include dials, slider switches, joysticks, click wheels, and the like.” The following paragraph, [0048] specifies that these buttons activate the surveillance system 300.)
Horn is not relied on for the below claim language.
However, Merwaday teaches a motorcycle provided with a battery for motorcycle activation (Merwaday, [0061] “In most implementations, the EV 1310 includes a battery 1080 … .” [0285] “Examples of “vehicles” include … motorcycles.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply the teachings of Merwaday to the teachings of Horn such that Merwaday’s system is used with Horn to expand Horn’s monitoring capabilities for traffic violations (Horn, abstract) to include Merwaday’s road usage monitoring (Merwaday, abstract) for the purpose of expanding revenue collection from traffic tickets to include charging based on road usage. Merwaday, [0003]-[0005]. Merwaday also teaches implementation details, such as the use of a battery for an electric vehicle.
Based on the above, this is an example of “combining prior art elements according to known methods to yield predictable results.” MPEP 2143.
2. The AI identification motorcycle with its control system of claim 1, wherein the motorcycle electric switch is further electrically connected with at least a protection device, a motorcycle power load, a motorcycle voltage and current regulation device, and the motorcycle generator is electrically connected to the motorcycle voltage and current regulation device. (Horn, [0037] “Alternatively, the imaging devices 104 can connect to another power source and/or be powered via reusable energy technologies, such as solar power.” Horn’s solar teaches the claimed generator. The broadest reasonable interpretation of the adjective motorcycle includes the various items being on a motorcycle, not necessarily the motorcycle themselves.)
3. The AI identification motorcycle with its control system of claim 1, wherein the AI device is further electrically connected to a wireless network bridge (router) or the AI device has a built-in 5G Wifi module. (Horn, [0095] “wireless systems (such as Wi-Fi®.” Horn was filed during the 5th generation of Wifi.)
4. The AI identification motorcycle with its control system of claim 3, wherein the wireless network bridge (router) serves as a wireless connection between the AI device and other external peripheral equipment, the external peripheral equipment can be a smart mobile phone or smart glasses as need, (Horn, [0050] “Examples of a suitable computing device may include personal computers, smartphones”)
with the App installed on the smart mobile phone or provided specifically for smart glasses, a linked two-way communication with the AI device is activated, and a real-scene image captured by the camera on the mobile phone or glasses is acquired, transmitted, through WebRTC software or other mobile phone image wireless communication mechanism, to the AI device for an image recognition analysis, followed by providing an analysis recognition result returned to the smart mobile phone or smart glasses. (Horn, abstract, “Advantageously, the surveillance system can record, analyze, detect, and communicate distracted driver violations effectively and efficiently.” Fig. 3B teaches the claimed App.)
5. The AI identification motorcycle with its control system of claim 1, wherein the AI device is electrically connected to a temperature and voltage detection device, the temperature and voltage detection device can conduct a two-way communication with the AI device through a USB port and an interface software, and the temperature and voltage detection device detects the temperature/voltage/current values of the first image acquisition device, the second image acquisition device, and the display device for comparison with safety factor values set by the AI device, and in turn, air intake and air exhausting of the heat dissipation device are driven, such that the accommodation cabin forms a convective airflow to lower down the temperature. (Merwaday, [0184] “A battery monitor/charger 2082 may be included in the compute node 2000 to track various measurements and/or metrics of the battery 2080 (“battery parameters”) such as, for example, voltage (e.g., minimum and/or maximum cell voltage) … temperature, … temperature monitoring measurements/metrics, … .”)
6. The AI identification motorcycle with its control system of claim 1, wherein a first image acquisition device, which is electrically connected to the AI device, the first image acquisition device comprising a first image acquisition card, the first image acquisition card being installed on a head of the motorcycle, and the first image acquisition card being electrically connected with the first image acquisition device through a coaxial cable transmission signal by an analog image signal input terminal, such that a digital image signal output terminal of the first image acquisition device is electrically connected with the AI device by signal transmission through a wire; a second image acquisition device, which is electrically connected to the AI device, the second image acquisition device comprising a second image acquisition card, the second image acquisition card being installed on a head of the motorcycle, and the second image acquisition card being electrically connected with the second image acquisition device through a coaxial cable transmission signal by an analog image signal input terminal, such that a digital image signal output terminal of the second image acquisition device is electrically connected with the AI device by signal transmission through a wire. (Horn, [0099] “Communication may be implemented using wireless or wired capability such as cable, fiber optics, a phone line, a cellular phone link, radio waves or other communication channels.”)
8. The AI identification motorcycle with its control system as claim 6, wherein a RFID active receiver, which is electrically connected to the AI device and installed on a head of the motorcycle, the RFID active receiver being connected with a RS485 port of the AI device through a UTP signal line, or can be connected with a RS232 port of the AI device via a RS485/RS232 converter, or can be connected with a USB port of the AI device via a RS485/USB converter, and the RFID active receiver can conduct receiving for ETC/eTag chips on parked vehicles with respect to roadside parking billing when the motorcycle is traveling, and cooperate with license plate recognition functions of the image acquisition devices to calculate a speed of each traveling vehicle and a matched license plate number in real time by means of an image analysis algorithm. (Merwaday, [0017] “The passive infrastructure-based implementations uses sensors (e.g., cameras, RFID sensor, and/or any other suitable sensor(s) such as those discussed herein) to detect the identity of the vehicle (e.g., based on license plate number, RFID tags, and/or the like), and calculates the road usage charge and/or provides such information to the road usage monitor for processing.”)
11. An AI identification vehicle with its control system, wherein a license plate recognition control system for the AI vehicle, including: a vehicle of motorcycle provided with a battery for motorcycle activation, an AI device electrically connected to the battery for motorcycle activation, a first image acquisition device electrically connected to the AI device, a second image acquisition device electrically connected to the AI device, the AI device being provided in an accommodation cabin of the motorcycle, the first image acquisition device and the second image acquisition device being installed on both right and left side of a head of the motorcycle respectively; (mapped as per claim 1)
the AI device cooperating with the first image acquisition device and the second image acquisition device to perform a computation of a license plate number recognition; which is characterized: (Horn, [0011] “The one or more imaging devices may be a camera, a license plate reader or a combination of both.”)
the computation of the license plate recognition including the following steps:
step 1: plate image input, in which at least one plate image is obtained from the first image acquisition device or the second image acquisition device at first and input to the AI device; (Horn, [0032] “As shown in FIG. 1A, imaging device 104 may be configured to monitor license plate information”)
step 2: license plate detection, in which a position, a size of a plate frame and an inclination angle of characters on a license plate in the plate image are detected based on a neural network plate detection algorithm, and the detected plate is cut out from the plate image; (Horn, [0060] “A second section 316 may be configured to zoom in on the image or recording of the first section 314.” [0043] “In one embodiment, LPR system 214 may be a Leonardo ELSAG Mobile Plate Hunter™ automatic license plate reader.” Horn’s ELSAG device teaches the claimed neural network.)
step 3: rotation correction, in which classification of the inclination angle of characters on the license plate is determined according to the step 2 to perform the rotation correction for the license plate in the plate image, such that texts on the license plate do not overlap as much as possible in a horizontal alignment; (Horn, [0078] “The additional data (time, date, position, orientation) may be stored along with image data, or may be stored in a separate portion of memory.”)
step 4: plate number recognition, in which the plate image after the rotation correction is input into a license plate identification neural network to recognize the plate number. (Horn, [0043] “In one embodiment, LPR system 214 may be a Leonardo ELSAG Mobile Plate Hunter™ automatic license plate reader.”)
17. The AI identification vehicle with its control system of claim 11, wherein the AI device is provided with a scratch pad memory, a software storage hard disk and a data storage hard disk, by which installation for running program is available and recognition images are stored. (Horn, [0012] “The surveillance system may further include data processing logic that is operatively coupled to a memory”)
Claims 18-23 and 25 are rejected as per their counterpart claims.
27. The AI identification motorcycle with its control system of claim 18, the AI identification motorcycle operating cooperatively with a roadside parking billing computing platform, the parking information being uploaded to a parking space database module of a roadside parking billing computing center via a wireless communication network by the wireless transmission output unit, followed by calculating a parking fee via a parking fee calculation module, and then transmitting the parking fee information to a user by a query and issuance module, the user comprising a parking fee toll and a driver. (Horn, [0009] “an imaging device of a mobile unit is configured to monitor and record traffic violations.” Horn’s genus of traffic violations teaches, or at least renders obvious, the claimed parking information because the genus of traffic violations is traditionally divided into moving and non-moving violations. MPEP 2144.08. Alternatively, they are known substitutes. MPEP 2144.06.)
Claim 28 is rejected as per claim 27.
Claims 29 and 30 are rejected as per their counterpart claims. See, e.g., claims 11 and 18 for claim 30.
31. The AI identification vehicle with its control system of claim 11, wherein a separable convolution can be performed for depths of the license plate detection algorithm of the neural network in the step 2, to characterize the license plate in the plate image from 512 by 512 to a smaller size gradually, and a prediction is performed for six of these depths through a prediction layer. (Merwaday, [0150] “deep CNN (DCN).” See also [0017] that this is used to read a license plate. Merwaday’s “deep” teaches the claimed separate convolutions (because they are understood as layers of convolution, and “deep” means having many layers.)
32. The AI identification vehicle with its control system of claim 11, wherein a size of the first prediction layer is 32 by 32, a size of the second prediction layer is 16 by 16, a size of the third prediction layer is 8 by 8, a size of the fourth prediction layer is 4 by 4, a size of the fifth prediction layer is 2 by 2, a size of the sixth prediction layer is 1 by 1, the location and the inclination angle classification of the license plate in the plate image are obtained for cutting from a scene in accordance with coordinates and rotation correction to complete preprocessing of license plate recognition. (Merwaday, [0150] “deep CNN (DCN).” See also [0017] that this is used to read a license plate. Merwaday’s “deep” teaches the claimed separate convolutions (because they are understood as layers of convolution, and “deep” means having many layers.)
33. The AI identification vehicle with its control system of claim 11, wherein the inclination angles in the step 3 are divided into 8 categories, in which two groups are from 0 degree to 10 degrees from left to right, two groups are from 10 degrees to 20 degrees from left to right, two groups are from 20 degrees to 30 degrees from left to right, and two groups are above 30 degrees, respectively, to cut the detected license plate out of the plate image. (Horn, [0043] “In one embodiment, LPR system 214 may be a Leonardo ELSAG Mobile Plate Hunter™ automatic license plate reader.” The claim’s “to cut” is understood as an intended use. The division of the inclination angles are not used by the claim because claim 11 specifies that this is done by the CNN rather than the algorithm of claim 33.)
34. The AI identification vehicle with its control system of claim 11, wherein the license plate number recognition in the step 4 is to recognize a plate string result for the preprocessed plate image by a license plate recognition algorithm of a plate recognition network. (Horn, [0043] “In one embodiment, LPR system 214 may be a Leonardo ELSAG Mobile Plate Hunter™ automatic license plate reader.”)
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
The technology described in Applicant’s abstract (combining license plate recognition to automatically bill drivers) was in wide use in the United States prior to the earliest asserted filing date. See, e.g., Wikipedia’s “Video tolling” article from May 25, 2023, retrieved from https://en.wikipedia.org/w/index.php?title=Video_tolling&oldid=1156893687 (copy previously attached).
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 DAVID ORANGE whose telephone number is (571)270-1799. The examiner can normally be reached Mon-Fri, 9-5.
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, Gregory Morse can be reached at 571-272-3838. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/DAVID ORANGE/Primary Examiner, Art Unit 2663
