Content Based Image Hashing Via Wavelet and Radon Transform

Image hash function based on the image content has applications in watermarking, authentication and image retrieval. This paper presents an algorithm for generating an image hash that is robust against content-preserving modifications and at the same time, is capable of detecting malicious tampering. Robust features are first extracted from the discrete wavelet transform followed by the Radon transform. Probabilistic quantization is then used to map the feature values to a binary sequence. Results show that the proposed method can resist perceptually insignificant modifications such as compression, filtering, scaling and rotation. It is also able to successfully detect content changing attacks such as insertion of foreign objects.