Abbas M. Al-Ghaili, S. Mashohor, A. Ismail, A. Ramli
{"title":"Efficient Implementation of VEDA for Highlighting Car License Plate Details","authors":"Abbas M. Al-Ghaili, S. Mashohor, A. Ismail, A. Ramli","doi":"10.1109/ICFCC.2009.35","DOIUrl":null,"url":null,"abstract":"Vertical edge detection is a very important task for image processing-based applications. One of the most common techniques which depends on this task is car license plate detection system. In this work, two contributions are presented and discussed. The first one, a Vertical Edge Detection Algorithm (VEDA) is proposed in order to extract vertical edges. The second one, an implementation of VEDA is presented in order to confirm that VEDA is robust for highlighting car license plates efficiently. The results show that VEDA is faster than Sobel and its time complexity is less. So, VEDA can be used with real-time applications. VEDA shows that it could detect vertical license plate details efficiently.","PeriodicalId":338489,"journal":{"name":"2009 International Conference on Future Computer and Communication","volume":"205 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Future Computer and Communication","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICFCC.2009.35","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
Vertical edge detection is a very important task for image processing-based applications. One of the most common techniques which depends on this task is car license plate detection system. In this work, two contributions are presented and discussed. The first one, a Vertical Edge Detection Algorithm (VEDA) is proposed in order to extract vertical edges. The second one, an implementation of VEDA is presented in order to confirm that VEDA is robust for highlighting car license plates efficiently. The results show that VEDA is faster than Sobel and its time complexity is less. So, VEDA can be used with real-time applications. VEDA shows that it could detect vertical license plate details efficiently.
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