{"title":"Design of a Configurable ATR System Using MATLAB","authors":"E. Wright, J. Northern","doi":"10.1109/TPSD.2008.4562741","DOIUrl":null,"url":null,"abstract":"Highly efficient and adaptable image recognition systems have become a high priority within the last decade due to terrorism. This paper describes a design and development process for a configurable automatic target recognition system. Our novel template matching system employs a Matlab algorithm developed to accurately detect object patterns within a JPEG image. After downloading the original JPEG image, the Matlab algorithm processes it in three sequential phases: 1) \"Sobel\" edge detection of the original image 2) Grey- level template matching based on the squared Euclidean distance theory and 3) Statistical pattern recognition of the resulting convoluted image. For our test cases, the cross correlation was determined using a template library created for the algorithm's image recognition process. The average runtime for our system ranges from 5-8 minutes, per test case, with 100% correct recognition using the template matching technique described.","PeriodicalId":410786,"journal":{"name":"2008 IEEE Region 5 Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE Region 5 Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TPSD.2008.4562741","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Highly efficient and adaptable image recognition systems have become a high priority within the last decade due to terrorism. This paper describes a design and development process for a configurable automatic target recognition system. Our novel template matching system employs a Matlab algorithm developed to accurately detect object patterns within a JPEG image. After downloading the original JPEG image, the Matlab algorithm processes it in three sequential phases: 1) "Sobel" edge detection of the original image 2) Grey- level template matching based on the squared Euclidean distance theory and 3) Statistical pattern recognition of the resulting convoluted image. For our test cases, the cross correlation was determined using a template library created for the algorithm's image recognition process. The average runtime for our system ranges from 5-8 minutes, per test case, with 100% correct recognition using the template matching technique described.