Novel feature extraction technique for the recognition of handwritten digits Article Swipe

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Computer science Normalization (sociology) Chain code Numeral system Numerical digit Pattern recognition (psychology) Feature extraction Digit recognition Artificial intelligence Support vector machine Feature vector Feature (linguistics) Speech recognition Image (mathematics) Artificial neural network Arithmetic Mathematics Anthropology Sociology Philosophy Linguistics

Abdelhak Boukharouba , Abdelhak Bennia ·

YOU? · · 2015 · Open Access · · DOI: https://doi.org/10.1016/j.aci.2015.05.001 · OA: W415355213

This paper presents an efficient handwritten digit recognition system based on support vector machines (SVM). A novel feature set based on transition information in the vertical and horizontal directions of a digit image combined with the famous Freeman chain code is proposed. The main advantage of this feature extraction algorithm is that it does not require any normalization of digits. These features are very simple to implement compared to other methods. We evaluated our scheme on 80,000 handwritten samples of Persian numerals and we have achieved very promising results.