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Abstract
Image hashing is an emerging technology in multimedia security. It uses a short string called image hash to represent an input image and finds applications in image authentication, tamper detection, digital watermark, image indexing, content-based image retrieval and image copy detection. This paper presents a hashing algorithm based on the observation that block entropies are approximately linearly changed after content-preserving manipulations. This is done by converting the input image to a fixed size, dividing the normalised image into non-overlapping blocks, extracting entropies of image blocks and applying a single-level 2D discrete wavelet transform to perform feature compression. Correlation coefficient is exploited to evaluate similarity between hashes. Experimental results show that the proposed algorithm is robust against content-preserving operations, such as JPEG compression, watermark embedding, Gamma correction, Gaussian low-pass filtering, adjustments of brightness and contrast, scaling and small angle rotation. Similarity values between hashes of different images are small, indicating good performances in discriminative capability.
This work was partially supported by the Scientific Research Foundation of Guangxi Normal University for Doctors, the Natural Science Foundation of China (60963008), the Guangxi Natural Science Foundation (2011GXNSFD018026, 0832104), the Project of the Education Administration of Guangxi (200911MS55) and the Scientific Research and Technological Development Program of Guangxi (10123005–8). The authors would like to thank the anonymous referees for their valuable comments and suggestions.