{"title":"A copy-move forgery detection system using approximation image local binary pattern","authors":"Daljeet Kaur Kalsi, P. Rai","doi":"10.1109/RISE.2017.8378168","DOIUrl":null,"url":null,"abstract":"During the past few years, digital image forgery detection system has been received a significant attention in the field of analyzing and understanding digital images. A copy-move forgery is introduced in images by copying a part of an image and put it in the same image or in the other image. In this paper, we proposed a system that detects a copy-move forgery in the images. The method involves feature extraction, feature matching, and duplicate block identification. In this paper, AILBP (Approximation image local binary pattern) method is being applied for feature extraction. The number of experiments is initiated on a standard standalone image. The experimental results indicate that the proposed system is effective enough to give high performance in terms of speed and accuracy.","PeriodicalId":166244,"journal":{"name":"2017 International Conference on Recent Innovations in Signal processing and Embedded Systems (RISE)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Recent Innovations in Signal processing and Embedded Systems (RISE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RISE.2017.8378168","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
During the past few years, digital image forgery detection system has been received a significant attention in the field of analyzing and understanding digital images. A copy-move forgery is introduced in images by copying a part of an image and put it in the same image or in the other image. In this paper, we proposed a system that detects a copy-move forgery in the images. The method involves feature extraction, feature matching, and duplicate block identification. In this paper, AILBP (Approximation image local binary pattern) method is being applied for feature extraction. The number of experiments is initiated on a standard standalone image. The experimental results indicate that the proposed system is effective enough to give high performance in terms of speed and accuracy.