{"title":"缺陷检测的超复相关","authors":"Shipeng Xie","doi":"10.1109/MVHI.2010.210","DOIUrl":null,"url":null,"abstract":"The normalized cross correlation (NCC) has been used extensively in machine vision for industrial inspection, but the traditional NCC suffers from false alarms for a complicated image that contains partial uniform regions. In this paper, new algorithms of hypercomplex correlation are proposed. We set up a color object model in hypercomplex domain, which provides integrated color characteristics of the object. The proposed hypercomplex correlation in color image can effectively alleviate false alarms in defect detection applications.","PeriodicalId":34860,"journal":{"name":"HumanMachine Communication Journal","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2010-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Hypercomplex Correlation for Defect Detection\",\"authors\":\"Shipeng Xie\",\"doi\":\"10.1109/MVHI.2010.210\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The normalized cross correlation (NCC) has been used extensively in machine vision for industrial inspection, but the traditional NCC suffers from false alarms for a complicated image that contains partial uniform regions. In this paper, new algorithms of hypercomplex correlation are proposed. We set up a color object model in hypercomplex domain, which provides integrated color characteristics of the object. The proposed hypercomplex correlation in color image can effectively alleviate false alarms in defect detection applications.\",\"PeriodicalId\":34860,\"journal\":{\"name\":\"HumanMachine Communication Journal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-04-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"HumanMachine Communication Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MVHI.2010.210\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"HumanMachine Communication Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MVHI.2010.210","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Social Sciences","Score":null,"Total":0}
The normalized cross correlation (NCC) has been used extensively in machine vision for industrial inspection, but the traditional NCC suffers from false alarms for a complicated image that contains partial uniform regions. In this paper, new algorithms of hypercomplex correlation are proposed. We set up a color object model in hypercomplex domain, which provides integrated color characteristics of the object. The proposed hypercomplex correlation in color image can effectively alleviate false alarms in defect detection applications.
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