Research Article

Multipurpose Perceptual Image Hashing Based on Block Truncation Coding

This study presents a new multipurpose image hashing scheme based on Block Truncation Coding (BTC). Vector Quantization (VQ) and BTC are both block-based lossy image compression techniques for gray-level images, but BTC can maintain the mean and standard deviation after compression. In our scheme, the original gray-level image is first partitioned into non-overlapping small blocks. BTC is then performed on each block to yield two mean values, i.e., a lower mean and a higher mean, as well as a bit plane. The relationship between two mean values are utilized to generate the intermediate binary image for copyright protection, while the number of ‘1’s in the bit plane is compared with a threshold to generate the intermediate binary image for content authentication. Finally, the authentication mark and permuted copyright logo are respectively XOR-ed with the two intermediate binary images to obtain final authentication and protection fingerprints. Because BTC is a fast encoding scheme, our proposed method is therefore with lower complexity compared to VQ-based multipurpose image hashing schemes. Experimental results demonstrate the effectiveness and efficiency of the proposed scheme.

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Mei-Lei Lv and Zhe-Ming Lu, 2011. Multipurpose Perceptual Image Hashing Based on Block Truncation Coding. Information Technology Journal, 10: 207-212.

DOI: 10.3923/itj.2011.207.212

URL: https://scialert.net/abstract/?doi=itj.2011.207.212

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Authors

Mei-Lei Lv

Zhe-Ming Lu

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Research Article

Multipurpose Perceptual Image Hashing Based on Block Truncation Coding

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