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Hybrid Features for an Arabic Word Recognition System
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作者 Mehmmood A. Abd sarab al rubeaai George Paschos 《Computer Technology and Application》 2012年第10期685-691,共7页
This research proposes and implements an Arabic Sub-Words Recognition System (ASWR). The system focuses on employing a combination of statistical and structural features to provide complete pattern's description an... This research proposes and implements an Arabic Sub-Words Recognition System (ASWR). The system focuses on employing a combination of statistical and structural features to provide complete pattern's description and enhances the recognition rate. Support Vector Machines (SVMs) is utilized as a promising pattern recognition tool. In addition to that, the problems of dots and holes are solved in a completely different way from the ones previously employed. The proposed system proceeds in several phases as follows: (1) image acquisition, (2) binarisation, (3) morphological processing, (4) feature extraction, which includes statistical features, i.e., moment invariants, and structural features, i.e., dot number, dot position, and number of holes, features, and (5) classification, using multi-class SVMs and applying a one-against-all technique. The proposed system has been tested using different sets of words and subwords and has achieved a nearly 98.90% recogiaition rate. Comparative results with NNs are also presented. 展开更多
关键词 Arabic word recognition support vector machines CLASSIFICATION feature extraction neural networks morphological.
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