Geometrically Robust Image Hash with Tamper Detection and Location

Image hashing is an effective approach to image authentication. In this paper, a geometric distortioninvariant image hashing scheme, which can detect and locate the tampering, is proposed. The reported scheme performs Polar Complex Exponential Transform (PCET) on an image, and then the magnitudes and the phases of PCETs are combined to generate a set of rotation and scaling invariant features. To address the issue of security, the PCET moments are weighted by secret key K1 and permuted by secret key K2 respectively. Then the key-dependent transformed feature space is used to calculate the image hash. If the test image is verified as tampered image in the verification process, a map of the estimated tampering can be reconstructed from the image hashes to locate the tampering regions. Experimental results show that this scheme can tolerate almost all the typical image processing manipulations such as geometric distortion, JPEG compression, blurring, noise addition, and enhancement. Besides robustness, the proposed hashing scheme has the ability of detecting minute tampering with localization of the tampered area.

[1]  Alfred Menezes,et al.  Handbook of Applied Cryptography , 2018 .

[2]  Shih-Fu Chang,et al.  A robust content based digital signature for image authentication , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[3]  Min Wu,et al.  Robust and secure image hashing , 2006, IEEE Transactions on Information Forensics and Security.

[4]  Raveendran Paramesran,et al.  Efficient computation of radial moment functions using symmetrical property , 2006, Pattern Recognit..

[5]  Vishal Monga,et al.  Perceptual Image Hashing Via Feature Points: Performance Evaluation and Tradeoffs , 2006, IEEE Transactions on Image Processing.

[6]  Zen Chen,et al.  A Zernike Moment Phase-Based Descriptor for Local Image Representation and Matching , 2010, IEEE Transactions on Image Processing.

[7]  Xudong Jiang,et al.  Two-Dimensional Polar Harmonic Transforms for Invariant Image Representation , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[8]  Mohammed Yakoob Siyal,et al.  A secure and robust hash-based scheme for image authentication , 2010, Signal Process..

[9]  Yanqiang Lei,et al.  Robust image hash in Radon transform domain for authentication , 2011, Signal Process. Image Commun..

[10]  Yan Zhao.  Perceptual Image Hash Using Texture and Shape Feature , 2012 .

[11]  Xiamu Niu,et al.  Robust Image Hashing Based on Random Gabor Filtering and Dithered Lattice Vector Quantization , 2012, IEEE Transactions on Image Processing.