Passive-Blind Image and Video Forgery Detection

• Main Authors: Cheng-Shian Lin, 林承賢
• Other Authors: Jyh-Jong Tsay
• Format: Others
• Language: en_US
• Published: 2015
• Online Access: http://ndltd.ncl.edu.tw/handle/9w39xu

博士 === 國立中正大學 === 資訊工程研究所 === 103 === Passive image/video forgery detection aims to detect the traces of tamping without prior information, and it has been widely used to provide essential evidences in many diverse areas, ranging from mainstream media, journalism and scientific publication, to medical imaging, criminal investigations and surveillance systems, to name a few. First, passive forgery detection for JPEG compressed image based on block size estimation and consistency analysis is proposed. 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. For overcoming these problems, 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. We finally perform a refinement process to eliminate false detections and fill in undetected tampered blocks. Second, passive approach for effective detection and localization of region-level video forgery with spatio-temporal coherence analysis is proposed. Most of current passive approaches either work only for frame-level detection and cannot localize region-level forgery, or suffer from high false detection rates for localization of tampered regions. In this thesis, we investigate two common region-level inpainting methods for object removal, temporal copy-and-paste and exemplar-based texture synthesis, and propose a new approach based on spatio-temporal coherence analysis for detection and localization of tampered regions. Our approach can handle camera motion and multiple object removal. Experiments show that our approach outperforms previous approaches, and can effectively detect and localize regions tampered by temporal copy-and-paste and texture synthesis. Finally, passive forgery detection for double compressed JPEG images using DCT coefficient analysis is proposed. Most current passive approaches either work only for image-level double JPEG compression detection and cannot localize region-level forgery, or suffer from high false detection rates in localizing altered regions. In this thesis, we investigate two common image formats for saving tampered image, uncompressed and JPEG compressed format, and proposed an effective approach based on DCT coefficient analysis for the detection and localization of altered regions from JPEG compressed images. Our approach can handle the tampered JPEG image resaved in JPEG compressed format with different quality factors. Experiments with various tampering methods such as copy-and-paste, image completion and composite tampering, show that the proposed approach is able to effectively detect and localize altered areas.