文章基本信息

标题：Handwritten Character Recognition Using Multiresolution Technique and Euclidean Distance Metric
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作者：Dileep Kumar Patel ; Tanmoy Som ; Sushil Kumar Yadav 等
期刊名称：Journal of Signal and Information Processing
印刷版ISSN：2159-4465
电子版ISSN：2159-4481
出版年度：2012
卷号：3
期号：2
页码：208-214
DOI：10.4236/jsip.2012.32028
出版社：Scientific Research Publishing
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.
关键词：Discrete Wavelet Transform; Euclidean Distance Metric; Feature Extraction; Handwritten Character Recognition; Bounding Box; Mean Vector