Off-line Handwritten Chinese Character Recognition Based On Bandelet

Off-line handwritten Chinese character recognition research has important meaning to Chinese character information processing automation and new generation computer's intelligent input .The research on off-line handwritten Chinese characters machine recognition has not only important theoretical value, but also wide market prospect.Based on researching the current OCR systems and related technologies, the paper presents the Recognition of Off-line handwritten signature verification and similar handwritten Chinese characters based on second generation bandelet. The works are as following.Off-line handwritten signature verification (HSV) is hard because it depends on only static information of image and dynamic information in writing process nearly fully disappeared. Facing the characters of Off-line HSV, this paper proposes a method based on bandelet tansform. It combines structure feature with statistical feature, extracted eigenvector is compressed by K-L transform. At last, true signature and forge signature are distinguished through support vector machines (SVM). The experimental results demonstrate the algorithm presented here reaches satisfied identical rate for testing stylebook.The bandelet transform not only has wavelet's main characteristic multiscale and time frequency localization ,but also has high direction and anisotropism. The bandelet transform which provides a sort of new image representation, can make full use of intrinsic geometric regularity and provide optimal representation for geometry regular image .Aim at similer character's abundance stroke direction, a new recognition method based on bandelet transform and support vector machines is provided. This method can real express character's structure feature and increase similer character recognition rate .Results of experiments show that this method is efficiency.