纺织品图像中的图案分割

Andreea Smoaca, D. Coltuc, V. Lazarescu
{"title":"纺织品图像中的图案分割","authors":"Andreea Smoaca, D. Coltuc, V. Lazarescu","doi":"10.1109/ISSCS.2009.5206185","DOIUrl":null,"url":null,"abstract":"This paper presents some results regarding the automatic segmentation of patterns in images of textile samples. The pattern segmentation is necessary for further extraction of a set of shape descriptors to be used in a CBIR database for textiles. Five different filters for removing the fabrics texture have been tested: mean, median, Gaussian, soft wavelet thresholding and a new approach based on Wavelet Transform and Independent Components Analysis. For segmentation, due to the poor color content of the images, the binarization proved to be a satisfactory choice. Three algorithms for the threshold computation have been tested: Otsu, background symmetry and triangle.","PeriodicalId":277587,"journal":{"name":"2009 International Symposium on Signals, Circuits and Systems","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Pattern segmentation in textile images\",\"authors\":\"Andreea Smoaca, D. Coltuc, V. Lazarescu\",\"doi\":\"10.1109/ISSCS.2009.5206185\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents some results regarding the automatic segmentation of patterns in images of textile samples. The pattern segmentation is necessary for further extraction of a set of shape descriptors to be used in a CBIR database for textiles. Five different filters for removing the fabrics texture have been tested: mean, median, Gaussian, soft wavelet thresholding and a new approach based on Wavelet Transform and Independent Components Analysis. For segmentation, due to the poor color content of the images, the binarization proved to be a satisfactory choice. Three algorithms for the threshold computation have been tested: Otsu, background symmetry and triangle.\",\"PeriodicalId\":277587,\"journal\":{\"name\":\"2009 International Symposium on Signals, Circuits and Systems\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-07-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Symposium on Signals, Circuits and Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSCS.2009.5206185\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Symposium on Signals, Circuits and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSCS.2009.5206185","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

摘要

本文介绍了纺织品样品图像中图案自动分割的一些结果。图案分割是进一步提取一组用于纺织品CBIR数据库的形状描述符所必需的。测试了五种不同的去除织物纹理的滤波方法:均值、中值、高斯、软小波阈值和基于小波变换和独立分量分析的新方法。对于分割,由于图像的颜色含量较差,二值化被证明是一种令人满意的选择。测试了三种阈值计算算法:Otsu、背景对称和三角形。
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
Pattern segmentation in textile images
This paper presents some results regarding the automatic segmentation of patterns in images of textile samples. The pattern segmentation is necessary for further extraction of a set of shape descriptors to be used in a CBIR database for textiles. Five different filters for removing the fabrics texture have been tested: mean, median, Gaussian, soft wavelet thresholding and a new approach based on Wavelet Transform and Independent Components Analysis. For segmentation, due to the poor color content of the images, the binarization proved to be a satisfactory choice. Three algorithms for the threshold computation have been tested: Otsu, background symmetry and triangle.
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
Chaos modulation communication channel: A case study A 2.4 GHz high-gain low noise amplifier Modified Ω′ metric for QPP interleavers depending on SNR Information fusion for obstacle recognition in visible and infrared images Graph drawing alogorithms based module placement
×
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:604180095
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