{"title":"Automatic edge detection in noisy fringe patterns","authors":"M. Ratnam","doi":"10.1109/ISSPA.2001.949795","DOIUrl":null,"url":null,"abstract":"Fringe patterns are usually analyzed using a predefined window due to the difficulty associated with finding their edges. This is because the fringes usually have minimum intensities similar to that of the background and therefore it is difficult to determine where a fringe starts and ends. This paper presents an automatic technique for detecting the edges of a noisy fringe pattern with various noise levels. The technique uses classical morphological operators and a simple binary edge detector. The relationship between background noise and threshold for the binarization was determined from simulated fringe patterns.","PeriodicalId":236050,"journal":{"name":"Proceedings of the Sixth International Symposium on Signal Processing and its Applications (Cat.No.01EX467)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Sixth International Symposium on Signal Processing and its Applications (Cat.No.01EX467)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSPA.2001.949795","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

Fringe patterns are usually analyzed using a predefined window due to the difficulty associated with finding their edges. This is because the fringes usually have minimum intensities similar to that of the background and therefore it is difficult to determine where a fringe starts and ends. This paper presents an automatic technique for detecting the edges of a noisy fringe pattern with various noise levels. The technique uses classical morphological operators and a simple binary edge detector. The relationship between background noise and threshold for the binarization was determined from simulated fringe patterns.
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在噪声条纹图案自动边缘检测
由于难以找到边缘,条纹图案通常使用预定义的窗口进行分析。这是因为条纹通常具有与背景相似的最小强度,因此很难确定条纹的开始和结束位置。本文提出了一种自动检测具有不同噪声水平的噪声条纹图边缘的技术。该技术使用经典形态学算子和简单的二进制边缘检测器。根据模拟的条纹图确定背景噪声与二值化阈值之间的关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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