图像纹理分析的超局部二值模式

Yiu-ming Cheung, Junping Deng
{"title":"图像纹理分析的超局部二值模式","authors":"Yiu-ming Cheung, Junping Deng","doi":"10.1109/SPAC.2014.6982701","DOIUrl":null,"url":null,"abstract":"Local Binary Pattern (LBP) is a simple yet powerful method for image feature extraction in pattern recognition and image processing. However, the LBP operator of each pixel mainly depends on its neighboring pixels and emphasizes on local information too much. From the practical viewpoint, the information is quite limited if we consider the LBP operator in isolation, especially for a large image. To deal with this issue, we propose ultra LBP (U-LBP), which consider the relationship among different LBP operators. The proposed method cannot only get the local but also ultra local information. The effectiveness of the proposed algorithm is investigated on gender recognition and digit recognition, respectively. The experimental results show that the proposed method outperforms the traditional LBP.","PeriodicalId":326246,"journal":{"name":"Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Ultra local binary pattern for image texture analysis\",\"authors\":\"Yiu-ming Cheung, Junping Deng\",\"doi\":\"10.1109/SPAC.2014.6982701\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Local Binary Pattern (LBP) is a simple yet powerful method for image feature extraction in pattern recognition and image processing. However, the LBP operator of each pixel mainly depends on its neighboring pixels and emphasizes on local information too much. From the practical viewpoint, the information is quite limited if we consider the LBP operator in isolation, especially for a large image. To deal with this issue, we propose ultra LBP (U-LBP), which consider the relationship among different LBP operators. The proposed method cannot only get the local but also ultra local information. The effectiveness of the proposed algorithm is investigated on gender recognition and digit recognition, respectively. The experimental results show that the proposed method outperforms the traditional LBP.\",\"PeriodicalId\":326246,\"journal\":{\"name\":\"Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SPAC.2014.6982701\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPAC.2014.6982701","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10

摘要

局部二值模式(LBP)是模式识别和图像处理中一种简单而强大的图像特征提取方法。然而,每个像素的LBP算子主要依赖于其相邻像素,过于强调局部信息。从实际应用的角度来看,如果孤立地考虑LBP算子,特别是对于大图像,得到的信息是非常有限的。为了解决这一问题,我们提出了考虑不同LBP算子之间关系的超LBP (U-LBP)算法。该方法既能获取局部信息,又能获取超局部信息。研究了该算法在性别识别和数字识别方面的有效性。实验结果表明,该方法优于传统的LBP算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Ultra local binary pattern for image texture analysis
Local Binary Pattern (LBP) is a simple yet powerful method for image feature extraction in pattern recognition and image processing. However, the LBP operator of each pixel mainly depends on its neighboring pixels and emphasizes on local information too much. From the practical viewpoint, the information is quite limited if we consider the LBP operator in isolation, especially for a large image. To deal with this issue, we propose ultra LBP (U-LBP), which consider the relationship among different LBP operators. The proposed method cannot only get the local but also ultra local information. The effectiveness of the proposed algorithm is investigated on gender recognition and digit recognition, respectively. The experimental results show that the proposed method outperforms the traditional LBP.
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
期刊最新文献
A new GPR image de-nosing method based on BEMD Design and implementation of one vertical video search engine Multi-scale sparse denoising model based on non-separable wavelet Dollar bill denomination recognition algorithm based on local texture feature Class specific dictionary learning for face recognition
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1