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Research on Recognition Method of Handwritten Numerals Segmentation based on B-P Neural Network
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作者 ningfang wei 《International Journal of Technology Management》 2013年第1期112-114,共3页
We propose a binarization method based pigment in the ZIP code of 24 bmp image simulation and digital identification by CCD sensors, were extracted the grid binary, image of zip code box and message of the two charact... We propose a binarization method based pigment in the ZIP code of 24 bmp image simulation and digital identification by CCD sensors, were extracted the grid binary, image of zip code box and message of the two characters binary image: analyze the image processing, which includes code frame edge detection and separation of the image binarization, denoising smoothing, tilt correction, the extraction code number, position, normalization processing, digital image thinning, character recognition feature extraction. Through testing, the recognition rate of this method can be over 90%. The recognition time of characters for character is less than 1.3 second, which means the method is of more effective recognition ability and can better satisfy the real system requirements. 展开更多
关键词 fuzzy recognition BP neural network zip code
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Research on Recognition Method of Handwritten Numerals Segmentation based on B-P Neural Network
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作者 ningfang wei 《International Journal of Technology Management》 2013年第7期64-66,共3页
We propose a binarization method based pigment in the ZIP code of 24 bmp image simulation and digital identification by CCD sensors, were extracted the grid binary image of zip code box and message of the two characte... We propose a binarization method based pigment in the ZIP code of 24 bmp image simulation and digital identification by CCD sensors, were extracted the grid binary image of zip code box and message of the two characters binary image; analyze the image processing, which includes code frame edge detection and separation of the image binarization, denoising smoothing, tilt correction, the extraction code number, position, normalization processing, digital image thinning, character recognition feature extraction. Through testing, the recognition rate of this method can be over 90%. The recognition time of characters for character is less than 1.3 second, which means the method is of more effective recognition ability and can better satisfy the real system requirements. 展开更多
关键词 fuzzy recognition: BP neural network zip code
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