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.
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. 10. The method of claim 1 further comprising automatically removing said local background variation to reveal an underlying pattern by said quantization transformation to efficiently manage a high dimensionality feature vector.