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| 求助论文“Fabric defect image segmentation based on visual attention mechanism of wavelet domain”是否SCI检索？ |
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baiyuefei
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sina1300841: 金币+3, ★★★很有帮助 2014-08-28 19:11:05
感谢参与，应助指数 +1
sina1300841: 金币+3, ★★★很有帮助 2014-08-28 19:11:05
2楼2014-08-28 18:37:48
baiyuefei
版主 (文学泰斗)
风雪
- LS-EPI: 1647
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sina1300841: 金币+3, ★★★很有帮助 2014-08-28 19:10:18
sunshan4379: LS-EPI+1, 感谢应助！ 2014-08-28 19:33:38
sina1300841: 金币+3, ★★★很有帮助 2014-08-28 19:10:18
sunshan4379: LS-EPI+1, 感谢应助！ 2014-08-28 19:33:38
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Fabric defect image segmentation based on the visual attention mechanism of the wavelet domain 作者:Guan, SQ (Guan, Shengqi)[ 1 ] ; Gao, ZY (Gao, Zhaoyuan)[ 1 ] TEXTILE RESEARCH JOURNAL 卷: 84 期: 10 页: 1018-1033 DOI: 10.1177/0040517513517964 出版年: JUN 2014 查看期刊信息 摘要 In order to explore the accurate image segmentation of fabric defects, we will introduce the visual attention mechanism of the wavelet domain to the dynamic detection of fabric defects. First of all, feature maps are formed by extracting simple features from a collection image. Secondly, feature maps by multi-layer wavelet decomposition are decomposed into a lot of feature sub-maps of the wavelet domain. On this basis, the center-surround operator among feature sub-maps of the wavelet domain is adopted to build the feature difference sub-maps, which are fused into feature saliency maps through fuse strategy. Finally, the defect interest areas are segmented based on the maximum between-cluster variance method in saliency maps, and the fabric defects through the region growing method are detected in the defect interest areas. Comparing with the wavelet transform algorithm, experimental results show that the proposed method is able to segment the defect information completely, and it has a strong ability to resist noise interference, which can improve the accuracy of defect detection. 关键词 作者关键词:wavelet domain; visual attention mechanism; feature saliency map; image segmentation KeyWords Plus:INSPECTION 作者信息 通讯作者地址: Guan, SQ (通讯作者) Xian Polytech Univ, Coll Mech & Elect Engn, 19 South Rd, Xian, Peoples R China. 地址: [ 1 ] Xian Polytech Univ, Coll Mech & Elect Engn, Xian, Peoples R China 电子邮件地址:sina1300841@163.com 基金资助致谢 基金资助机构 授权号 Scientific Research Program - Shan xi Provincial Education Department 2013JK1083 Doctoral scientific Research - Xi'an Polytechnic University BS1005 查看基金资助信息 出版商 SAGE PUBLICATIONS LTD, 1 OLIVERS YARD, 55 CITY ROAD, LONDON EC1Y 1SP, ENGLAND 类别 / 分类 研究方向:Materials Science Web of Science 类别:Materials Science, Textiles 文献信息 文献类型:Article 语种:English 入藏号: WOS:000338014400002 ISSN: 0040-5175 电子 ISSN: 1746-7748 期刊信息 Impact Factor (影响因子): Journal Citation Reports® 其他信息 IDS 号: AJ9FZ Web of Science 核心合集中的 "引用的参考文献": 22 Web of Science 核心合集中的 "被引频次": 0 引文网络 0 被引频次 22 引用的参考文献 查看 Related Records 查看引证关系图 创建引文跟踪 (数据来自 Web of ScienceTM 核心合集) 全部被引频次计数 0 / 所有数据库 0 / Web of Science 核心合集 0 / BIOSIS Citation Index 0 / 中国科学引文数据库 0 / Data Citation Index 0 / SciELO Citation Index 此记录来自: Web of ScienceTM 核心合集 建议修正 如果希望提高此记录中数据的质量，请提供修正建议。 |
3楼2014-08-28 18:37:59
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