教師資料查詢 | 類別: 期刊論文 | 教師: 林承賢 CHENG SHIAN LIN (瀏覽個人網頁)

標題:Passive forgery detection for JPEG compressed image based on block size estimation and consistency analysis
學年
學期
出版(發表)日期2015/03/15
作品名稱Passive forgery detection for JPEG compressed image based on block size estimation and consistency analysis
作品名稱(其他語言)
著者Cheng-Shian Lin; Jyh-Jong Tsay
單位
出版者
著錄名稱、卷期、頁數Applied Mathematics & Information Sciences 9(2), p.1015–1028
摘要As most of digital cameras and image capture devices do not have modules for embedding watermark or signature, passive forgery detection which aims to detect the traces of tamping without embedded information has become the major focus of recent research for JPEG compressed image. However, our investigation shows that current approaches for detection and localization of tampered areas are very sensitive to image contents, and suffer from high false detection rates for localization of tampered areas for images with intensive edges and textures. In this paper, we present an effective approach which overcomes above problem, using reliable estimation and analysis of block sizes from the block artifacts resulting in JPEG compression process. We first propose an enhanced cross difference filter to strengthen block artifacts and reduce interference from edges and textures, and then integrate techniques from random sampling, voting and maximum likelihood method to improve the accuracy of block size estimation. We develop two different random sampling strategies for block size estimation: one for estimation of the primary JPEG block size, and the other for consistency analysis of local block sizes. Local blocks whose JPEG block sizes are different from the primary block size are classified as tampered blocks. We finally perform a refinement process to eliminate false detections and fill in undetected tampered blocks. Experiment over various tampering methods such as copy-and-paste, image completion and composite tampering, shows that our approach can effectively detect and localize tampered areas, and is not sensitive to image contents such as edges and textures.
關鍵字Passive image forgery detection;JPEG compression;JPEG block artifact extraction;maximum likelihood estimation
語言英文
ISSN2325-0399
期刊性質國外
收錄於SCI;
產學合作
通訊作者Lin, Cheng-shian
審稿制度
國別巴林
公開徵稿
出版型式,電子版
相關連結
SDGs
Google+ 推薦功能,讓全世界都能看到您的推薦!