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首页> 外文期刊>International journal of computational vision and robotics >Automatic extraction, segmentation and recognition of multi-font Indian Pincode
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Automatic extraction, segmentation and recognition of multi-font Indian Pincode

机译:自动提取,分割和识别多字体印度Pincode

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摘要

This paper proposes a new algorithm for Pincode script identification (PSI) that would detect Pincode in the address image of the envelope. The developed system differentiates the scripts of English alphabets and numerals. A new method for normalisation of extracted chain code features is proposed. The extracted numerals of various font types (multi-font) were recognised using multi layer perceptron (MLP) with back propagation (BP) algorithm and Naive Bayes classifier (NBC). The recognised Pincode was used for automating the sorting process. The experimental results of recognition of isolated Pincode were discussed. Recognition accuracy of 95% for MLP-BP and 93.8% for NBC was obtained. The performance comparison of MLP-BP and NBC are discussed in this paper.
机译:本文提出了一种用于Pincode脚本识别(PSI)的新算法,该算法将检测信封的地址图像中的Pincode。开发的系统区分英语字母和数字的脚本。提出了一种新的归一化链码特征归一化方法。使用带有反向传播(BP)算法和朴素贝叶斯分类器(NBC)的多层感知器(MLP)识别各种字体类型(多字体)的提取数字。识别出的Pincode用于自动排序过程。讨论了识别孤立的Pincode的实验结果。 MLP-BP的识别准确度为95%,NBC的识别准确度为93.8%。本文讨论了MLP-BP和NBC的性能比较。

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