Novel feature extraction technique for the recognition of handwritten digits

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• 作者：Abdelhak Boukharouba^a ; ^{boukharouba_abdelhak@hotmail.com} ; Abdelhak Bennia^b
• 关键词：Feature extraction ; Feature selection ; Digit recognition ; Support vector machine
• 刊名：Applied Computing and Informatics
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：13
• 期：1
• 页码：19-26
• 全文大小：737 K
• 卷排序：13

文摘

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.