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Separating Indic Scripts with matra for Effective Handwritten Script Identification in Multi-Script Documents

机译:使用matra分隔印度语脚本,以在多脚本文档中有效地识别手写脚本

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摘要

We present a novel approach for separating Indic scripts with 'matra', which is used as a precursor to advance and/or ease subsequent handwritten script identification in multi-script documents. In our study, among state-of-the-art features and classifiers, an optimized fractal geometry analysis and random forest are found to be the best performer to distinguish scripts with 'matra' from their counterparts. For validation, a total of 1204 document images are used, where two different scripts with 'matra': Bangla and Devanagari are considered as positive samples and the other two di r erent scripts: Roman and Urdu are considered as negative samples. With this precursor, an overall script identification performance can be advanced by more than 5.13% in accuracy and 1.17 times faster in processing time as compared to conventional system.
机译:我们提出了一种新颖的方法来用“ matra”分隔印度文字,它被用作在多脚本文档中提高和/或简化后续手写脚本识别的先驱。在我们的研究中,在最先进的特征和分类器中,优化的分形几何分析和随机森林被认为是区分带有“ matra”的脚本与对应脚本的最佳性能。为了进行验证,总共使用了1204个文档图像,其中两个带有'matra'的不同脚本:Bangla和Devanagari被视为正样本,另外两个不同的脚本:Roman和Urdu被视为负样本。与传统系统相比,使用此前体,可以将整体脚本识别性能提高5.11%以上的精度,并在处理时间上加快1.17倍。

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