{"title":"A concurrent modified algorithm for Generalized Hough Transform","authors":"T. Achalakul, S. Madarasmi","doi":"10.1109/ICIT.2002.1189300","DOIUrl":null,"url":null,"abstract":"This paper presents a novel concurrent algorithm for object detection based on the Hough Transform. The Generalized Hough Transform can detect object contours regardless of scale and orientation, but has a computational complexity of O(N/sup 2/RS), where N, R, and S are the array dimensions for X/Y, rotation, and scale, respectively. The high complexity makes it impossible to perform object detection in real-time. In our work, we propose a modified, concurrent algorithm using a multi-threading technique with manager-worker scheme to obtain a reduced complexity of O(N/sup 2//M) where M is the number of processors. Our new algorithm utilizes multi-threading technology to enhance the computing speed. The algorithm is evaluated from both the perspective of output image quality and performance scalability.","PeriodicalId":344984,"journal":{"name":"2002 IEEE International Conference on Industrial Technology, 2002. IEEE ICIT '02.","volume":"109 2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2002 IEEE International Conference on Industrial Technology, 2002. IEEE ICIT '02.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIT.2002.1189300","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
This paper presents a novel concurrent algorithm for object detection based on the Hough Transform. The Generalized Hough Transform can detect object contours regardless of scale and orientation, but has a computational complexity of O(N/sup 2/RS), where N, R, and S are the array dimensions for X/Y, rotation, and scale, respectively. The high complexity makes it impossible to perform object detection in real-time. In our work, we propose a modified, concurrent algorithm using a multi-threading technique with manager-worker scheme to obtain a reduced complexity of O(N/sup 2//M) where M is the number of processors. Our new algorithm utilizes multi-threading technology to enhance the computing speed. The algorithm is evaluated from both the perspective of output image quality and performance scalability.