基于边缘检测和关联规则的纹理分类

M. Karabatak, A. Şengur, M. C. Ince
{"title":"基于边缘检测和关联规则的纹理分类","authors":"M. Karabatak, A. Şengur, M. C. Ince","doi":"10.1109/SIU.2006.1659696","DOIUrl":null,"url":null,"abstract":"Texture can be defined as a local statistical pattern of texture primitives in observer's domain of interest. Texture classification aims to assign texture labels to unknown textures, according to training samples and classification rules. Association rules capture both structural and statistical information, and automatically identify the structures that occur most frequently and relationships that have significant discriminative power. So, association rules can be adapted to capture frequently occurring local structures in textures. This paper describes the usage of association rules for texture classification problem. The performed experimental studies show the effectiveness of the association rules","PeriodicalId":415037,"journal":{"name":"2006 IEEE 14th Signal Processing and Communications Applications","volume":"14 10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Texture Classification Using Edge Detection and Association Rules\",\"authors\":\"M. Karabatak, A. Şengur, M. C. Ince\",\"doi\":\"10.1109/SIU.2006.1659696\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Texture can be defined as a local statistical pattern of texture primitives in observer's domain of interest. Texture classification aims to assign texture labels to unknown textures, according to training samples and classification rules. Association rules capture both structural and statistical information, and automatically identify the structures that occur most frequently and relationships that have significant discriminative power. So, association rules can be adapted to capture frequently occurring local structures in textures. This paper describes the usage of association rules for texture classification problem. The performed experimental studies show the effectiveness of the association rules\",\"PeriodicalId\":415037,\"journal\":{\"name\":\"2006 IEEE 14th Signal Processing and Communications Applications\",\"volume\":\"14 10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-04-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 IEEE 14th Signal Processing and Communications Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SIU.2006.1659696\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 IEEE 14th Signal Processing and Communications Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIU.2006.1659696","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

纹理可以定义为纹理原语在观察者感兴趣的区域的局部统计模式。纹理分类的目的是根据训练样本和分类规则为未知纹理分配纹理标签。关联规则捕获结构信息和统计信息,并自动识别出现最频繁的结构和具有显著判别能力的关系。因此,关联规则可以用于捕获纹理中频繁出现的局部结构。本文描述了关联规则在纹理分类问题中的应用。实验研究表明了该关联规则的有效性
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Texture Classification Using Edge Detection and Association Rules
Texture can be defined as a local statistical pattern of texture primitives in observer's domain of interest. Texture classification aims to assign texture labels to unknown textures, according to training samples and classification rules. Association rules capture both structural and statistical information, and automatically identify the structures that occur most frequently and relationships that have significant discriminative power. So, association rules can be adapted to capture frequently occurring local structures in textures. This paper describes the usage of association rules for texture classification problem. The performed experimental studies show the effectiveness of the association rules
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