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I am working on handwritten character recognition using neural networks. Currently I have segmented each character from the image. Now I want to extract features of each character so that I can feed them to the neural network. So what features should I extract from each character image?. Please suggest any sample code or procedure.

user3561600
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  • possible duplicate of [Which features can i use for handwritten OCR other than a downsampled binary grid of the image?](http://stackoverflow.com/questions/12888600/which-features-can-i-use-for-handwritten-ocr-other-than-a-downsampled-binary-gri) – Rafael Monteiro Apr 26 '14 at 19:16

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I am not sure if you should extract features from the characters. All the classic an novel methods feed the ANN using a downsampled version of the binary image that contains the character.

One example (1993) is this. There they use a 8x8 pixel version of the character as the ANN input. The question that @rafael-monteiro suggest in the comments also states that.

If your input images are big, maybe you want to try this method, or if you desire to extract some features, this work proposes some features, for exampl the angle of rotation of the parts of the character with more points or the aspect ratio of the character.

phyrox
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