基于模板匹配的波斯语/阿拉伯语手写体数字识别特征提取

Ninth International Conference on Document Analysis and Recognition (ICDAR 2007) Pub Date : 2007-12-17 DOI:10.1109/ICDAR.2007.273

M. Ziaratban, K. Faez, F. Faradji

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引用次数: 49

摘要

本文开发了一种基于模板匹配的手写体波斯语/阿拉伯语数字识别系统。模板匹配是检测和识别图像中目标的基本方法。在拟议的方法中，所选择的模板尽可能代表波斯语/阿拉伯语规定的书写形式的特点。实验结果表明，本文提出的基于语言的特征提取方法比其他常用的特征提取方法具有更高的性能。使用NM-MLP作为分类器，使用6000个样本进行训练。测试集包括4000个样本。该方法的识别率为97.65%，比Zernike矩法提高了0.64%。

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Language-Based Feature Extraction Using Template-Matching in Farsi/Arabic Handwritten Numeral Recognition

A recognition system based on template matching for identifying handwritten Farsi/Arabic numerals has been developed in this paper. Template matching is a fundamental method of detecting the presence of objects and identifying them in an image. In the proposed method, templates have been chosen so that they represent the features of FARSI/Arabic prescribed form of writing as possible. Experimental results show that the performance of proposed language-based method has been achieved more than the other usual common feature extraction approaches. NM-MLP is used as a classifier and trained with 6000 samples. Test set includes 4000 samples. The recognition rate of 97.65% was obtained, which is 0.64% more than Zernike moment approach.

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Ninth International Conference on Document Analysis and Recognition (ICDAR 2007)

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