{"title":"基于方向梯度直方图的图像不一致检测","authors":"M. Hilal, P. Yannawar, A. Gaikwad","doi":"10.1109/ICISIM.2017.8122141","DOIUrl":null,"url":null,"abstract":"Today there are various types of image editing tools which make totally changes in image with free of cost, Image has performed a significant role in Human life but image has easily fiddle using image processing software. Fiddle image has difficult to detect that it is original or not for this reasons the image forgery detection topic is active research work nowadays. The proposed of this paper to detect image inconsistency using Histogram of Orientated Gradient (HOG) method which help us to determining which block has manipulation of an images. The paper conducting with many stages namely acquisition, preprocessing, and feature extraction and matching the performance of this system are based on false accepted rate (FAR) and false reject rate (FRR)","PeriodicalId":139000,"journal":{"name":"2017 1st International Conference on Intelligent Systems and Information Management (ICISIM)","volume":"3 2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Image inconsistency detection using histogram of orientated gradient (HOG)\",\"authors\":\"M. Hilal, P. Yannawar, A. Gaikwad\",\"doi\":\"10.1109/ICISIM.2017.8122141\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Today there are various types of image editing tools which make totally changes in image with free of cost, Image has performed a significant role in Human life but image has easily fiddle using image processing software. Fiddle image has difficult to detect that it is original or not for this reasons the image forgery detection topic is active research work nowadays. The proposed of this paper to detect image inconsistency using Histogram of Orientated Gradient (HOG) method which help us to determining which block has manipulation of an images. The paper conducting with many stages namely acquisition, preprocessing, and feature extraction and matching the performance of this system are based on false accepted rate (FAR) and false reject rate (FRR)\",\"PeriodicalId\":139000,\"journal\":{\"name\":\"2017 1st International Conference on Intelligent Systems and Information Management (ICISIM)\",\"volume\":\"3 2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 1st International Conference on Intelligent Systems and Information Management (ICISIM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICISIM.2017.8122141\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 1st International Conference on Intelligent Systems and Information Management (ICISIM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICISIM.2017.8122141","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Image inconsistency detection using histogram of orientated gradient (HOG)
Today there are various types of image editing tools which make totally changes in image with free of cost, Image has performed a significant role in Human life but image has easily fiddle using image processing software. Fiddle image has difficult to detect that it is original or not for this reasons the image forgery detection topic is active research work nowadays. The proposed of this paper to detect image inconsistency using Histogram of Orientated Gradient (HOG) method which help us to determining which block has manipulation of an images. The paper conducting with many stages namely acquisition, preprocessing, and feature extraction and matching the performance of this system are based on false accepted rate (FAR) and false reject rate (FRR)