{"title":"基于Canny边缘检测器的图像伪造检测分析","authors":"S. Jadhav, Neha Ramlal Shelot","doi":"10.1109/aimv53313.2021.9670931","DOIUrl":null,"url":null,"abstract":"As now-a-days many image processing software and editing tools are available using which image can be easily faked. In various fields digital images are used as legal evidence, for forensics investigations,, so there is need of making such system that can detect image forgery. The passive approach of image forgery detection provides image authencity without having any information about the digital image. Further in this paper we have discussed various forgery techniques which were used for creating forgeries in the digital picture. We proposed an optimized method that can detect the forgery in the image using k-means and feature matching algorithm which uses canny edge detector. It gives recall between 85 to 95% and precision 100%.We run this system over two datasets.","PeriodicalId":135318,"journal":{"name":"2021 International Conference on Artificial Intelligence and Machine Vision (AIMV)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Analysis of Image Forgery Detection Using Canny Edge Detector\",\"authors\":\"S. Jadhav, Neha Ramlal Shelot\",\"doi\":\"10.1109/aimv53313.2021.9670931\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As now-a-days many image processing software and editing tools are available using which image can be easily faked. In various fields digital images are used as legal evidence, for forensics investigations,, so there is need of making such system that can detect image forgery. The passive approach of image forgery detection provides image authencity without having any information about the digital image. Further in this paper we have discussed various forgery techniques which were used for creating forgeries in the digital picture. We proposed an optimized method that can detect the forgery in the image using k-means and feature matching algorithm which uses canny edge detector. It gives recall between 85 to 95% and precision 100%.We run this system over two datasets.\",\"PeriodicalId\":135318,\"journal\":{\"name\":\"2021 International Conference on Artificial Intelligence and Machine Vision (AIMV)\",\"volume\":\"52 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-09-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Conference on Artificial Intelligence and Machine Vision (AIMV)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/aimv53313.2021.9670931\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Artificial Intelligence and Machine Vision (AIMV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/aimv53313.2021.9670931","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analysis of Image Forgery Detection Using Canny Edge Detector
As now-a-days many image processing software and editing tools are available using which image can be easily faked. In various fields digital images are used as legal evidence, for forensics investigations,, so there is need of making such system that can detect image forgery. The passive approach of image forgery detection provides image authencity without having any information about the digital image. Further in this paper we have discussed various forgery techniques which were used for creating forgeries in the digital picture. We proposed an optimized method that can detect the forgery in the image using k-means and feature matching algorithm which uses canny edge detector. It gives recall between 85 to 95% and precision 100%.We run this system over two datasets.