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Character Recognition for Cursive English Handwriting to Recognize Medicine Name from Doctor's Prescription

机译:草书英文手写字符识别,可从医生处方中识别出医学名称

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This paper aims to represent the work related to character recognition for cursive English handwriting recognition. Recognition of cursive characters is very challenging because the characters are connected to each other. In the proposed architecture, horizontal projection method is used for text-line segmentation and vertical projection histogram method is used for word segmentation. Convex hull algorithm is used for feature extraction and SVM is used for classification. Proposed work is specifically for medical domain to recognize the medicine name from doctor's prescription. The segmentation experiments are carried out on different doctor's prescription samples and achieved 95% accuracy for text-line segmentation and 92% accuracy for word segmentation. The recognition accuracy of proposed system is 85%.
机译:本文旨在介绍与草书英语手写识别中的字符识别相关的工作。草书字符的识别非常具有挑战性,因为字符是相互连接的。在所提出的体系结构中,水平投影方法用于文本线分割,垂直投影直方图方法用于字分割。凸包算法用于特征提取,而SVM用于分类。拟议的工作专门针对医学领域,以便从医生的处方中识别出药物名称。分割实验是在不同的医生处方样本上进行的,文本线分割的准确度达到95%,单词分割的准确度达到92%。所提出系统的识别精度为85%。

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