DETAILED ACTION
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 21, 25,26, 31, 34, 35 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Wang (WO 2015184899).
Regarding claim 21 Wang teaches a license plate detection and recognition system, the system comprising:
a processor circuit; and a memory circuit coupled to the processor circuit, the memory circuit including instructions that, when executed by the processor circuit, configure the system ( Abstract, device for recognizing a license plate of a vehicle) to:
detect at least one vehicle in a plurality of image frames, and detect one or more regions in the at least one vehicle including a license plate of the at least one vehicle ( Page 4, Step 101: Identify image frames of a plurality of consecutive positions of the license plate in the screen acquisition range);
detect one or more clusters of characters in each of the detected regions r(Page 5, cluster-based segmentation), and identify a set of characters from the detected one or more clusters of characters (Page 4, Step 101: obtain identification data of the license plate when the plurality of consecutive positions are respectively obtained, Step 102: When the plurality of locations are counted, the identification data of the license plate obtains the recognition result of the license plate);
send the identified characters to a post-processor for temporal validation, wherein the post- processor is configured to analyze relative placement of the identified characters across the plurality of image frames ( Page 5, paragraph 2, The image frames of the plurality of consecutive positions may be image frames that are continuously played in the video, or may be image frames that are acquired by the photographing device at consecutively set time intervals; Paragraph 3, the license plate is in a plurality of consecutive positions within the screen acquisition range, and refers to a plurality of positions in which the license plate appears successively);
compute a weighted probability for a character among the identified characters using a confidence value for the character by multiplying the confidence value by a number of frames that recognized the character divided by a total number of frames considered ( Page 6, paragraph 3, For example, by recognizing seven image frames of seven successive positions of the license plate within the screen acquisition range; and obtaining identification data of the license plate at the seven consecutive positions, respectively. The identification data of the first to seventh image frames are: Beijing BEQ7C2, Beijing BF02C2, expensive BE0702, Yue BE07C2, Yue BF07C2, Yue BE07C2, Yue BE07C2, Yue BE07C2. The character recognition results of the seven character positions are respectively counted; if the first character position is identified as "Beijing" 2 times, the recognition as "expensive" has 1 time, and the recognition as "Yue" has 4 times); and
validate the character with a higher-weighted probability (Page 6,paragraph 3, it is considered that the final recognition result of the position is "Yue"; similarly, the recognition results of the second to seventh character positions are: "B", "E", "0", "7", "C", "2").
Regarding claim 25 Wang teaches the system of claim 21, wherein the system is configured to receive the image frames from at least one of an image capturing device ( Page 2, the license plate … of the captured image), a network, or a memory circuit.
Regarding claim 26 Wang teaches the system of claim 21, wherein the system is configured to detect the one or more regions in the image frames using at least one of an identified color, an identified edge(page 6, last paragraph, the image is gray-scale transformed, and the edge image is generated by edge detection using Sobel operator) , a transition in edges, a shape, a size, an orientation, a Histogram of Gradients (HoGs), or a machine learning-based classifier.
Claims 31, 34, 35 recite the method in the system of claims 21, 25, 26, and thus also rejected.
Claim Rejections - 35 USC § 103
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.
Claim(s) 22-24, 32, 33 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wang in view of Wang2 ( US20090208060).
.
Regarding claim 22 Wang teaches the system of claim 21.
Wang does not expressly teach wherein the post-processor is configured to discard characters that are identified as having a different alignment in a minority of frames.
However, Wang2 teaches discard characters that are identified as having a different alignment in a minority of frames([0022], removing the adornment before plate character segmentation).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of Wang and Wang2, by removing many adornment frames in Wang following the teaching for Wang2, with motivation “ dramatically reduces the amount of calculation and improves the efficiency” ( Wang2, [0022]).
Regarding claim 23 Wang teaches the system of claim 21.
Wang does not expressly teach
wherein the post-processor is configured to discard characters that are identified as having a different placement in a minority of frames.
However, Wang2 teaches to discard characters that are identified as having a different placement in a minority of frames ( [0023], The system will remove the “plate run” if it satisfies one of the following conditions: (1) the vertical height is larger than Hp; (2) the horizontal length is larger than Wp; and (3) the “plate run” is located between two other plate runs of which both lengths are larger than Wp. )
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of Wang and Wang2, by removing many adornment or “plate run” frames in Wang following the teaching for Wang2, with motivation to “avoid spending much time on calculation of the candidate regions”( Wang2,[0023]) and “ dramatically reduces the amount of calculation and improves the efficiency” ( Wang2, [0022]).
Regarding claim 24 Wang teaches the system of claim 21.
Wang does not expressly teach
wherein the post-processor is configured to identify one or more frames to discard and one or more frames to retain;
However, Wang2 teaches
to identify one or more frames to discard and one or more frames to retain ( [0023], The system will remove the “plate run” if it satisfies one of the following conditions: (1) the vertical height is larger than Hp; (2) the horizontal length is larger than Wp; and (3) the “plate run” is located between two other plate runs of which both lengths are larger than Wp. )
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of Wang and Wang2, by removing many adornment or “plate run” frames in Wang following the teaching for Wang2, with motivation to “avoid spending much time on calculation of the candidate regions”( Wang2,[0023]) “ dramatically reduces the amount of calculation and improves the efficiency” ( Wang2, [0022]).
Claims 32, 33 recite the method in the system of claims 22-24, and thus also rejected.
Claim(s)27-30, 36-40 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wang in view of in view of Li (CN 101937508)
Regarding claim 27, Wang teaches the system of claim 21.
Wang does not expressly teach wherein the system is configured to generate a candidate license plate using the identified characters and a license plate template that corresponds to a geographic location of the at least one detected vehicle.
However, Li teaches to generate a candidate license plate using the identified characters t([0059], character binary template base, comprising 37 Chinese character library, pinball capitalized English letter library and 10 digital library) and a license plate template that corresponds to a geographic location ( left most Chinese characters identified in Chinese license plates denote geographical locations).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of Wang an Li, by substituting the character recognition algorithm in Wang with that taught by Li, with motivation for “a high definition image of license plate location and recognition” ( Li, [0001]).
Regarding claim 28, Wang in view of Li teaches the system of claim 27, wherein the identified characters comprise alphanumeric characters, and the license plate template indicates a particular number or orientation of the alphanumeric characters that are expected in the candidate license plate ( Wang, page 7, last two paragraphs, all the character template features to be recognized is calculated … Yue BF07C2, Yue BE07C2, Yue BE07C2, Yue BE07C2).
Regarding claim 29, Wang in view of Li teaches the system of claim 27, wherein the system is configured to generate the candidate license plate by:
selecting the license plate template based on the geographic location of the detected at least one vehicle(Li, [0026], binarizing the vertical projection value 6 into position, to select projection and the small character right boundary of the divided position as character. This method can effectively solve the problem that the connected character and damaged character segmentation problem) ;
applying a classification algorithm(Li, [0033], SVM classifier) to populate a matrix of normalized confidence indicators corresponding to the identified characters([0032], dividing to obtain the character normalized to a width of 18 pixels and height of 36 pixels); and
using a confidence threshold and the matrix of confidences to build the candidate license plate by selecting particular characters for each of the identified characters that satisfies the confidence threshold(Li,[0017], these license plate character interval threshold; [0033], and outputting the corresponding confidence ) .
Regarding claim 30, Wang in view of Li teaches the system of claim 27, wherein the license plate template includes information about a likelihood of particular characters comprising the characters of the license plate of the detected at least one vehicle(Li, [0034], a template matching result and SVM prediction result two evidences, their respective credibility distribution function taking the confidence output by respectively taking 0 weight. 6 and 0. 4, whereby we can respectively calculate the template matching result confidence Hi (A1) after fusion and SVM result reliability of m (A2)).
Claims 36-37 recite the method in the system of claims 27-28, and thus also rejected
Claims 38-40 recite the similar subject matter in claim1 in combination with the system in claims 27-30, and thus also are rejected.
Conclusion
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JIANGENG SUN
Examiner
Art Unit 2661
/Jiangeng Sun/Examiner, Art Unit 2671 /Jiangeng Sun/Examiner, Art Unit 2671
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