A Novel Secure Image Hashing based on Reversible Watermarking for Forensic Analysis

Abstract. Nowadays, digital images and videos have become increasingly popular over the Internet and bring great social impact to a wide audience. In the meanwhile, technology advancement allows people to easily alter the content of digital multimedia and brings serious concern on the trustworthiness of online multimedia information. In this paper, we propose a new framework for multimedia forensics by using compact side information based on reversible watermarking to reconstruct the processing history of a multimedia data. Particularly, we focus on a secure reversible watermarking to make the image hash more secure and robust. Moreover, we introduce an algorithm based on Radon transform and scale space theory to effectively estimate the parameters of geometric transforms and to detect local tampering. The experimental results show that the quality of the embedded image is very high and the positions of the tampered parts are identified correctly

Design and Analysis of a Fragile Watermarking Scheme Based on Block-Mapping

Part 2: WorkshopInternational audienceDue to the wide variety of attacks and the difficulties of developing an accurate statistical model of host features, the structure of the watermark detector is derived by considering a simplified channel model. In this paper, we present a fragile watermarking based on block-mapping mechanism which can perfectly recover the host image from its tampered version by generating a reference data. By investigating characteristics of watermark detector, we make an effective analysis such as fragility against robustness measure and distinguish its property. In particular, we derive a watermark detector structure with simplified channel model which focuses on the error probability versus watermark-to-noise-ratio curve and describes a design by calculating the performance of technique, where attacks are either absent or as noise addition

A Region-based Robust 3D Face Recognition

We present a region-based robust 3D facerecognition approach which is robust to facialexpressions, illumination changes andocclusions. Facial surface is often deformed byexpressions. Generally, the mouth is the mostaffected by expressions, whereas the nose is theleast affected and the most static region. For thisreason, we have concentrated on locating thenose tip and segmenting the nose region. Ourmethod can be grouped into two types: Thesurface-based approach which uses curvatureinformation of the face and the statistical-basedapproach which uses subspace analysis. A newalgorithm based on the combination of these twotypes of approaches is presented in this paper.The algorithm extracts the curvature informationof the nose region from range image first, bydecomposing into maximum and minimumcurvature, and then applies PCA (PrincipalComponent Analysis) to reduce the dimension offeature space, respectively. The two features arefused using the sum rule. Our results show thatthe utilization of the cropped nose regionincreases the recognition accuracy up to 96.1percent, where a subset taken from GavabDBdatabase is used to make evaluations