Fractional Fourier transform as a signal processing tool: An overview of recent developments

Robustness and discrimination are two of the most important objectives in image hashing. We incorporate ring partition and invariant vector distance to image hashing algorithm for enhancing rotation robustness and discriminative capability. As ring partition is unrelated to image rotation, the statistical features that are extracted from image rings in perceptually uniform color space, i.e., CIE L*a*b* color space, are rotation invariant and stable. In particular, the Euclidean distance between vectors of these perceptual features is invariant to commonly used digital operations to images (e.g., JPEG compression, gamma correction, and brightness/contrast adjustment), which helps in making image hash compact and discriminative. We conduct experiments to evaluate the efficiency with 250 color images, and demonstrate that the proposed hashing algorithm is robust at commonly used digital operations to images. In addition, with the receiver operating characteristics curve, we illustrate that our hashing is much better than the existing popular hashing algorithms at robustness and discrimination.

Robust Image Hashing With Ring Partition and Invariant Vector Distance

A secure and robust hash-based scheme for image authentication

This paper designs an efficient image hashing with a ring partition and a nonnegative matrix factorization (NMF), which has both the rotation robustness and good discriminative capability. The key contribution is a novel construction of rotation-invariant secondary image, which is used for the first time in image hashing and helps to make image hash resistant to rotation. In addition, NMF coefficients are approximately linearly changed by content-preserving manipulations, so as to measure hash similarity with correlation coefficient. We conduct experiments for illustrating the efficiency with 346 images. Our experiments show that the proposed hashing is robust against content-preserving operations, such as image rotation, JPEG compression, watermark embedding, Gaussian low-pass filtering, gamma correction, brightness adjustment, contrast adjustment, and image scaling. Receiver operating characteristics (ROC) curve comparisons are also conducted with the state-of-the-art algorithms, and demonstrate that the proposed hashing is much better than all these algorithms in classification performances with respect to robustness and discrimination.

Robust Perceptual Image Hashing Based on Ring Partition and NMF

Robust signal hashing defines a feature vector that characterizes the signal, independently of "nonsignificant" distortions of its content. When dealing with images, the considered distortions are typically due to compression or small geometrical manipulations. In other words, robustness means that images that are visually indistinguishable should produce equal or similar hash values. To discriminate image contents, a hash function should produce distinct outputs for different images. Our paper first proposes a robust hashing algorithm for still images. It is based on radial projection of the image pixels and is denoted the Radial hASHing (RASH) algorithm. Experimental results provided on the USC-SIPI dataset reveal that the proposed RASH feature vector is more robust and provides much stronger discrimination than a conventional histogram-based feature vector. The RASH vector appears to be a good candidate to build indexing algorithms, copy-detection systems, or content-based authentication mechanisms. To take benefit from the RASH vector capabilities, video content is summarized into key frames, each of them characterizing a video shot and described by its RASH vector. The resulting video hashing system works in real time and supports most distortions due to common spatial and temporal video distortions.

Robust video hashing based on radial projections of key frames

Media hashing is an alternative approach to many applications previously accomplished with watermarking. The major disadvantage of the existing media hashing technologies is their limited resistance to geometric attacks. In this paper, a novel geometric distortion-invariant image hashing scheme, which can be employed to perform copy detection and content authentication of digital images, is proposed. Our major contributions are threefold: (i) a mesh-based robust hashing function is proposed; (ii) a sophisticated hash database for error-resilient and fast matching is constructed; and (iii) the application scalability of our scheme for content copy tracing and authentication is studied. In addition, we further investigate several media hashing issues, including robustness and discrimination, error analysis, and complexity, with respect to the proposed image hashing system. Exhaustive experimental results obtained from benchmark attacks confirm the excellent performance of the proposed method.

/pdf/geometric-distortion-resilient-image-hashing-scheme-and-its-1gi8dbuyeo.pdf

Geometric distortion-resilient image hashing scheme and its applications on copy detection and authentication

The major disadvantage of existing watermarking methods is their limited resistance to extensive geometric attacks. In addition, we have found that the weakness of multiple watermark embedding methods that were initially designed to resist geometric attacks is their inability to withstand the watermark-estimation attacks (WEAs), leading to reduce resistance to geometric attacks. In view of these facts, this paper proposes a robust image watermarking scheme that can withstand geometric distortions and WEAs simultaneously. Our scheme is mainly composed of three components: 1) robust mesh generation and mesh-based watermarking to resist geometric distortions; 2) construction of media hash-based content-dependent watermark to resist WEAs; and 3) a mechanism of false positive-oriented watermark detection, which can be used to determine the existence of a watermark so as to achieve a tradeoff between correct detection and false detection. Furthermore, extensive experimental results obtained using the standard benchmark (i.e., Stirmark) and WEAs, and comparisons with relevant watermarking methods confirm the excellent performance of our method in improving robustness. To our knowledge, such a thorough evaluation has not been reported in the literature before

Media Hash-dependent Image Watermarking Resilient Against Both Geometric Attacks and Estimation Attacks Based on False Positive-Oriented Detection

Due to the desired non-invasive property, non-data hiding (called media hashing here) is considered to be an alternative to achieve many applications previously accomplished with watermarking. Recently, media hashing techniques for content identification have been gradually emerging. However, none of them are really resistant against geometrical attacks. In this paper, our aim is to propose a geometry-invariant image hashing scheme, which can be employed for content copy detection and tracing. Our system is mainly composed of three components: (i) robust mesh extraction; (iii) mesh-based robust hash extraction; and (iii) hash matching for similarity measurement. Exhaustive experimental results obtained from benchmark attacks have confirmed the performance of the proposed method

/pdf/robust-mesh-based-hashing-for-copy-detection-and-tracing-of-3crh2zy0ka.pdf

Robust mesh-based hashing for copy detection and tracing of images

Media hash-dependent image watermarking resilient against both geometric attacks and estimation attacks based on false positive-oriented detection

Watermarking methods usually claim a certain degree of robustness against those attacks that aim to destroy the hidden watermark at the expense of degrading the quality of media data. However, there exist watermark-estimation attacks (WEAs), such as the collusion attack and copy attack that are clever at disclosing the hidden watermark for unauthorized purposes while maintaining media’s quality. The aim of this study was to deal with the WEA problem. We begin by gaining insight into WEA, leading to formal definitions of optimal watermark estimation and perfect cover data recovery. Subject to these definitions, the content-dependent watermark (CDW) is proposed to resist watermark-estimation attacks. The key is to introduce a media hash as a constituent component of the CDW. Mathematical analyses and experiment results consistently verify the effectiveness of the content-dependent watermarking scheme. To our knowledge, this anti-disclosure watermarking is the first work that takes resistance to both collusion and copy attacks into consideration.

Chao-Yong Hsu

Papers

Geometric distortion-resilient image hashing scheme and its applications on copy detection and authentication

Media Hash-dependent Image Watermarking Resilient Against Both Geometric Attacks and Estimation Attacks Based on False Positive-Oriented Detection

Robust mesh-based hashing for copy detection and tracing of images

Media hash-dependent image watermarking resilient against both geometric attacks and estimation attacks based on false positive-oriented detection

Content-Dependent Anti-disclosure Image Watermark