多部件自适应融合的手写体阿拉伯字符识别

doi:10.3969/j.issn.1001-2400.2012.06.003

Abstract

Abstract:

For 100 Arabic characters, a handwritten recognition algorithm based on radical decomposition and self-adaptive fusion is proposed. Firstly, the radical model is established by decomposing the Arabic character as three types of radicals: main, affix and dot. According to the analysis of connected strokes, a robust radical description is obtained. Secondly, different feature extractions and classifications are designed for various types of radicals, so that every radical is matched to detect and identify slight differences between similarities. Finally, a multi-radical fusion scheme based on the D-S evidence theory is developed. A new method to estimate the fusion coefficient is also proposed according to the confidence distribution of radicals. With the corresponding discounted mass refined based on the coefficient, all radicals can be self-adaptively fused to enhance character recognition effect. Analyses and experiments show that the proposed method can lead to a better performance than the present traditional algorithms.

Key words: handwriting recognition, Arabic language, information fusion, self-adaptive, evidence theory

XU Yamei;LU Zhaoyang;LI Jing. Multi-radical self-adaptive fusion method for handwritten Arabic character recognition[J].J4, 2012, 39(6): 16-21+77.

References

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Multi-radical self-adaptive fusion method for handwritten Arabic character recognition

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