基于区域加权行程长度特征的离线手写德文数字识别

P. Singh, Supratim Das, R. Sarkar, M. Nasipuri
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引用次数: 11

摘要

在过去的几十年里,人们对手写罗马文字和数字的识别进行了广泛的研究,其准确性达到了令人满意的状态。但在谈论印度最流行的文字之一Devanagari时,就不能这么说了。提出了一种高效的手写体梵文数字识别系统。该系统采用新颖的196元掩模定向(MOD)特征进行识别。该方法使用五种传统分类器在6000个手写数字样本上进行了测试。采用3重交叉验证方案,采用支持向量机(SVM)分类器,系统的识别准确率最高,达到95.02%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Recognition of offline handwriten Devanagari numerals using regional weighted run length features
Recognition of handwritten Roman characters and numerals has been extensively studied in the last few decades and its accuracy reached to a satisfactory state. But the same cannot be said while talking about the Devanagari script which is one of most popular script in India. This paper proposes an efficient digit recognition system for handwritten Devanagari script. The system uses a novel 196-element Mask Oriented Directional (MOD) features for the recognition purpose. The methodology is tested using five conventional classifiers on 6000 handwritten digit samples. On applying 3-fold cross-validation scheme, the proposed system yields the highest recognition accuracy of 95.02% using Support Vector Machine (SVM) classifier.
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