LICENSE PLATE OPTICAL CHARACTER RECOGNITION METHOD AND SYSTEM
First Claim
1. A method for recognizing a license plate character, said method comprising:
- capturing a license plate image with respect to a vehicle utilizing an image capturing unit and thereafter segmenting said license plate image into a license plate character image;
pre-processing said license plate character image to remove a local background variation with respect to said license plate character image and to define a local feature thereof utilizing a quantization transformation; and
identifying a classification margin for each character image utilizing a set of machine learning classifiers each binary in nature for said character image in order to thereafter determine a character type associated with at least one machine learning classifier among said set of machine learning classifiers with a largest classification margin to declare an optical character recognition result.
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Accused Products
Abstract
A method and system for recognizing a license plate character utilizing a machine learning classifier. A license plate image with respect to a vehicle can be captured by an image capturing unit and the license plate image can be segmented into license plate character images. The character image can be preprocessed to remove a local background variation in the image and to define a local feature utilizing a quantization transformation. A classification margin for each character image can be identified utilizing a set of machine learning classifiers each binary in nature, for the character image. Each binary classifier can be trained utilizing a character sample as a positive class and all other characters as well as non-character images as a negative class. The character type associated with the classifier with a largest classification margin can be determined and the OCR result can be declared.
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Citations
20 Claims
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1. A method for recognizing a license plate character, said method comprising:
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capturing a license plate image with respect to a vehicle utilizing an image capturing unit and thereafter segmenting said license plate image into a license plate character image; pre-processing said license plate character image to remove a local background variation with respect to said license plate character image and to define a local feature thereof utilizing a quantization transformation; and identifying a classification margin for each character image utilizing a set of machine learning classifiers each binary in nature for said character image in order to thereafter determine a character type associated with at least one machine learning classifier among said set of machine learning classifiers with a largest classification margin to declare an optical character recognition result. - View Dependent Claims (2, 3, 4, 5, 6, 8, 9, 10)
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7. The method of dam 1 wherein said set of machine learning classifiers comprises a set of split up sparse network of winnows machine learning image classifiers.
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11. A system for recognizing a license plate character, said system comprising:
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a processor; and a computer-usable medium embodying computer code, said computer-usable medium being coupled to said data bus, said computer program code comprising instructions executable by said processor and configured for; capturing a license plate image with respect to a vehicle utilizing an image capturing unit and thereafter segmenting said license plate image into a license plate character image; pre-processing said license plate character image to remove a local background variation with respect to said license plate character image and to define a local feature thereof utilizing a quantization transformation; and identifying a classification margin for each character image utilizing a set of machine learning classifiers each binary in nature for said character image in order to thereafter determine a character type associated with at least one machine learning classifier among said set of machine learning classifiers with a largest classification margin to declare an optical character recognition result. - View Dependent Claims (12, 13, 14, 15, 16, 17)
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18. A processor-readable medium storing code representing instructions to cause a processor to perform a process to recognize a license plate character, said code comprising code to:
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capture a license plate image with respect to a vehicle utilizing an image-capturing unit and thereafter segmenting said license plate image into a license plate character image; pre-process said license plate character image to remove a local background variation with respect to said license plate character image and to define a local feature thereof utilizing a quantization transformation; and identify a classification margin for each character image utilizing a set of machine learning classifiers each binary in nature for said character image in order to thereafter determine a character type associated with at least one machine learning classifier among said set of machine learning classifiers with a largest classification margin to declare an optical character recognition result. - View Dependent Claims (19, 20)
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Specification