一种有效的数字和字母字符识别方法

Yun Li, M. Xie
{"title":"一种有效的数字和字母字符识别方法","authors":"Yun Li, M. Xie","doi":"10.1109/ICCT.2008.4716212","DOIUrl":null,"url":null,"abstract":"An effective algorithm for number and letter character recognition is proposed in this paper. Our algorithm employs template matching, but it unlike traditional template matching method using the original pixel value to match. Our algorithm draws some features from the original image, and then obtains an eigenvector of 192 dimensions. Before drawing features, the image is disposed using math morphologic algorithm. And then measures the Euclidean distance between the sample vector and the template vector. Then we can obtain the result of recognition. A larger number of experiments prove that this algorithm own high performance and robustness. It can recognize characters which have high similarities, for example, 8, B, R, O and Q. This algorithm also tolerates the slightly tilt of the image. The recognition rate of this algorithm is 99.25%.","PeriodicalId":259577,"journal":{"name":"2008 11th IEEE International Conference on Communication Technology","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"An effective method for number and letter character recognition\",\"authors\":\"Yun Li, M. Xie\",\"doi\":\"10.1109/ICCT.2008.4716212\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An effective algorithm for number and letter character recognition is proposed in this paper. Our algorithm employs template matching, but it unlike traditional template matching method using the original pixel value to match. Our algorithm draws some features from the original image, and then obtains an eigenvector of 192 dimensions. Before drawing features, the image is disposed using math morphologic algorithm. And then measures the Euclidean distance between the sample vector and the template vector. Then we can obtain the result of recognition. A larger number of experiments prove that this algorithm own high performance and robustness. It can recognize characters which have high similarities, for example, 8, B, R, O and Q. This algorithm also tolerates the slightly tilt of the image. The recognition rate of this algorithm is 99.25%.\",\"PeriodicalId\":259577,\"journal\":{\"name\":\"2008 11th IEEE International Conference on Communication Technology\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-12-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 11th IEEE International Conference on Communication Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCT.2008.4716212\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 11th IEEE International Conference on Communication Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCT.2008.4716212","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

摘要

提出了一种有效的数字和字母字符识别算法。我们的算法采用模板匹配,但不同于传统的模板匹配方法使用原始像素值进行匹配。我们的算法从原始图像中提取一些特征,然后得到192维的特征向量。在绘制特征之前,使用数学形态学算法对图像进行处理。然后测量样本向量和模板向量之间的欧氏距离。然后我们可以得到识别的结果。大量的实验证明,该算法具有较高的性能和鲁棒性。它可以识别相似度高的字符,如8、B、R、O和q。该算法还可以容忍图像的轻微倾斜。该算法的识别率为99.25%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An effective method for number and letter character recognition
An effective algorithm for number and letter character recognition is proposed in this paper. Our algorithm employs template matching, but it unlike traditional template matching method using the original pixel value to match. Our algorithm draws some features from the original image, and then obtains an eigenvector of 192 dimensions. Before drawing features, the image is disposed using math morphologic algorithm. And then measures the Euclidean distance between the sample vector and the template vector. Then we can obtain the result of recognition. A larger number of experiments prove that this algorithm own high performance and robustness. It can recognize characters which have high similarities, for example, 8, B, R, O and Q. This algorithm also tolerates the slightly tilt of the image. The recognition rate of this algorithm is 99.25%.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信