Handwritten Character Recognition Using Multiresolution Technique and Euclidean Distance Metric

• 作者: Dileep Kumar Patel Manoj Kumar Singh Sushil Kumar Yadav Tanmoy Som
• 来源期刊: 信号与信息处理(英文)
• 学科: 工学
• 关键词: DISCRETE WAVELET TRANSFORM Euclidean DISTANCE Metric Feature Extraction Handwritten CHARACTER Recognition Bounding Box Mean Vector
• 年，卷（期）: 2012,（2）
• 页码范围: 208-214
• 页数: 7页
• 分类号: TP39

摘要

In the present paper, the problem of handwritten character recognition has been tackled with multiresolution technique using discrete wavelet transform (DWT) and Euclidean distance metric (EDM). The technique has been tested and found to be more accurate and faster. Characters is classified into 26 pattern classes based on appropriate properties. Features of the handwritten character images are extracted by DWT used with appropriate level of multiresolution technique, and then each pattern class is characterized by a mean vector. Distances from input pattern vector to all the mean vectors are computed by EDM. Minimum distance determines the class membership of input pattern vector. The proposed method provides good recognition accuracy of 90% for handwritten characters even with fewer samples.