文章基本信息

标题：Offline Handwritten Hindi SWARs Recognition using A Novel Wave based Feature Extraction Method
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作者：Ajay Indian ; Karamjit Bhatia
期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2017
卷号：14
期号：4
出版社：IJCSI Press
摘要：Offline handwritten character recognition is a very challenging area of research as handwriting of two persons may bear resemblance whereas handwriting of an individual may vary at different times. The character recognition accuracy depends on the ways the features are extracted from the samples and utilized to formulate the feature vector. In this paper, a novel technique TARANG for feature extraction is proposed to recognize offline handwritten Hindi SWARs (vowels). This technique for extracting features from an image is inspired by the natural movement of wave in a medium. A feature vector obtained by using proposed technique is used for the training of Backpropagation Neural Network and recognition rate as high as 96.2% is achieved.
关键词：Offline Handwritten Character Recognition; Feature Extraction; Global Features; Local Features; Back;propagation Neural Network