Holistic recognition of handwritten Tamil words

Thadchanamoorthy Subramaniam, U. Pal, H. Premaretne, N. Kodikara
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引用次数: 8

Abstract

In this paper, we describe a writer independent method for recognizing offline unconstrained handwritten Tamil words/strings. Touching and overlapping are main bottleneck of handwriting recognition and to overcome this, we adopted a holistic approach here. To handle various handwritings of different individuals, at first, some pieces of preprocessing work are done on an input word. Next, Gabor based features are computed on the processed word. These Gabor features along with other geometric features of the word image are then fed to an SVM classifier for recognition. In our experimental study, we have used 4270 samples (collected from the class of 217 country names) written in Tamil and obtained 86.36% recognition rate.
泰米尔语手写文字的整体识别
在本文中,我们描述了一种独立于书写器的离线无约束手写泰米尔语单词/字符串识别方法。触摸和重叠是手写识别的主要瓶颈,为了克服这一点,我们采用了一种整体的方法。为了处理不同人的不同笔迹,首先对输入字进行一些预处理工作。接下来,在处理后的单词上计算基于Gabor的特征。然后将这些Gabor特征与单词图像的其他几何特征一起馈送到支持向量机分类器进行识别。在我们的实验研究中,我们使用了4270个样本(从217个国家名称类别中收集)用泰米尔语书写,获得了86.36%的识别率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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