A robust soft hash algorithm for digital image signature

Abstract

Watermarking is largely used for copyright protection and fast search of images in databases. Another method for securely identifying images is to use hash functions. Digital Signature Standard, used in cryptosystem to dispute authentication documents, is based on hash functions. A digital signature is a bit stream dependent on key and content of document. For each document, the digital signature algorithm provides a unique output bit stream. In order to be efficient in images, the digital signature should be different if and only if the image content, and not the input bit stream, is different. Our new method is a one-way function for images. Using the Radon transform and Principal Component Analysis, we extract characteristics robust against geometrical transformation (rotation and scaling) and image processing attacks (compression, filtering, blurring).

Geometric distortion-resilient image hashing system and its application scalability

“…3, respectively. Our image hashing method is operated on normalized meshes such that geometric-resilience is not restricted to a ne transformations 11,12,25]. Our previous approaches proposed via this paradigm were reported in 7,18], and the capabilities of robustness and discrimination were obtained.…”

“…However, the two methods 5, 26] only achieve limited resistance to geometric distortions. In 11,12,25], image hashing methods were proposed based on the Radon transform and exploited its a ne invariance. However, resistance to geometric distortions was greatly limited if the incoming attacks went b e y ond a ne distortions.…”

A Survey on Image Hashing for Image Authentication

“…The image is firstly projected in Radon domain, then the median point of each projection of each angle [43], the PCA features on Radon vectors [44], and the low frequency DCT coefficients of radial variance vectors [45] are extracted separately for hash generations. While all the above Radon based hashing approaches are no key combined.…”

Robust Image Hashing Using Radon Transform and Invariant Features

“…Lin and Chang develop a hashing method based on discrete cosine transform (DCT) of non-overlapping image blocks, but the method is not tolerant to geometric distortions [4]. Lefebvre et al propose an image hashing method using the important features extracted in radon transform, which owns good robustness but lacks the ability to resist some conventional attacks [5], [6]. Lei et al describe a robust scheme using the radon transform and moments for generating hashing sequence [7].…”