局部方向模式(LDP)——一种用于目标识别的鲁棒图像描述符

T. Jabid, M. H. Kabir, O. Chae
{"title":"局部方向模式(LDP)——一种用于目标识别的鲁棒图像描述符","authors":"T. Jabid, M. H. Kabir, O. Chae","doi":"10.1109/AVSS.2010.17","DOIUrl":null,"url":null,"abstract":"This paper presents a novel local feature descriptor, theLocal Directional Pattern (LDP), for describing localimage feature. A LDP feature is obtained by computing theedge response values in all eight directions at each pixelposition and generating a code from the relative strengthmagnitude. Each bit of code sequence is determined byconsidering a local neighborhood hence becomes robust innoisy situation. A rotation invariant LDP code is alsointroduced which uses the direction of the most prominentedge response. Finally an image descriptor is formed todescribe the image (or image region) by accumulating theoccurrence of LDP feature over the whole input image (orimage region). Experimental results on the Brodatz texturedatabase show that LDP impressively outperforms theother commonly used dense descriptors (e.g.,Gabor-wavelet and LBP).","PeriodicalId":415758,"journal":{"name":"2010 7th IEEE International Conference on Advanced Video and Signal Based Surveillance","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"114","resultStr":"{\"title\":\"Local Directional Pattern (LDP) – A Robust Image Descriptor for Object Recognition\",\"authors\":\"T. Jabid, M. H. Kabir, O. Chae\",\"doi\":\"10.1109/AVSS.2010.17\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a novel local feature descriptor, theLocal Directional Pattern (LDP), for describing localimage feature. A LDP feature is obtained by computing theedge response values in all eight directions at each pixelposition and generating a code from the relative strengthmagnitude. Each bit of code sequence is determined byconsidering a local neighborhood hence becomes robust innoisy situation. A rotation invariant LDP code is alsointroduced which uses the direction of the most prominentedge response. Finally an image descriptor is formed todescribe the image (or image region) by accumulating theoccurrence of LDP feature over the whole input image (orimage region). Experimental results on the Brodatz texturedatabase show that LDP impressively outperforms theother commonly used dense descriptors (e.g.,Gabor-wavelet and LBP).\",\"PeriodicalId\":415758,\"journal\":{\"name\":\"2010 7th IEEE International Conference on Advanced Video and Signal Based Surveillance\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-08-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"114\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 7th IEEE International Conference on Advanced Video and Signal Based Surveillance\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AVSS.2010.17\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 7th IEEE International Conference on Advanced Video and Signal Based Surveillance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AVSS.2010.17","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 114

摘要

本文提出了一种新的局部特征描述符——局部定向模式(LDP),用于描述局部图像特征。通过计算每个像素位置上所有八个方向的边缘响应值并从相对强度大小生成代码来获得LDP特征。每个码位序列通过考虑局部邻域来确定,从而成为鲁棒噪声情况。介绍了一种旋转不变的LDP编码,该编码利用了最突出边缘响应的方向。最后,通过累积整个输入图像(或图像区域)上LDP特征的出现次数,形成图像描述符来描述图像(或图像区域)。在Brodatz纹理数据库上的实验结果表明,LDP显著优于其他常用的密集描述符(例如,Gabor-wavelet和LBP)。
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
Local Directional Pattern (LDP) – A Robust Image Descriptor for Object Recognition
This paper presents a novel local feature descriptor, theLocal Directional Pattern (LDP), for describing localimage feature. A LDP feature is obtained by computing theedge response values in all eight directions at each pixelposition and generating a code from the relative strengthmagnitude. Each bit of code sequence is determined byconsidering a local neighborhood hence becomes robust innoisy situation. A rotation invariant LDP code is alsointroduced which uses the direction of the most prominentedge response. Finally an image descriptor is formed todescribe the image (or image region) by accumulating theoccurrence of LDP feature over the whole input image (orimage region). Experimental results on the Brodatz texturedatabase show that LDP impressively outperforms theother commonly used dense descriptors (e.g.,Gabor-wavelet and 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
Statistical Background Modeling: An Edge Segment Based Moving Object Detection Approach Who, what, when, where, why and how in video analysis: an application centric view Trajectory Based Activity Discovery Local Abnormality Detection in Video Using Subspace Learning Functionality Delegation in Distributed Surveillance Systems
×
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