A Blind Indic Script Recognizer for Multi-script Documents

P. Pati, A. Ramakrishnan
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引用次数: 6

Abstract

We report a hierarchical blind script identifier for 11 different Indian scripts. An initial grouping of the 11 scripts is accomplished at the first level of this hierarchy. At the subsequent level, we recognize the script in each group. The various nodes of this tree use different feature-classifier combinations. A database of 20,000 words of different font styles and sizes is collected and used for each script. Effectiveness of Gabor and Discrete Cosine Transform features has been independently evaluated using nearest neighbor, linear discriminant and support vector machine classifiers. The minimum and maximum accuracies obtained, using this hierarchical mechanism, are 92.2% and 97.6%, respectively.
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用于多脚本文档的盲索引脚本识别器
我们报告了11种不同印度文字的分级盲文字标识符。11个脚本的初始分组是在这个层次结构的第一级完成的。在接下来的层次上,我们识别每一组中的脚本。该树的各个节点使用不同的特征分类器组合。收集了不同字体样式和大小的2万个单词的数据库,并用于每个脚本。使用最近邻、线性判别和支持向量机分类器对Gabor和离散余弦变换特征的有效性进行了独立评估。使用这种分层机制获得的最小和最大精度分别为92.2%和97.6%。
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