Robust Image Hashing

Robust Image Hashing

Daniela Coltuc (University Politehnica Bucharest, Romania)
Copyright: © 2015 |Pages: 11
DOI: 10.4018/978-1-4666-5888-2.ch592

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The hash calculation follows the two steps scheme in Figure 1, consisting in feature extraction and compression. At the end of the first step, the image is reduced at a feature vector called intermediate hash. The intermediate hash is transformed into a robust hash by quantization, binarization and compression. In RIH, the term compression is used purely to designate a significant reduction in the dimensionality of the feature vector. The techniques for obtaining compression in RIH are different from those used in traditional image compression, where the processing chain is quasi reversible in order to allow also the image decompression. In RIH, the reversibility is not necessary.

Figure 1.

RIH general scheme


Key Terms in this Chapter

Fragility: The hash property to change when the image cognitive content changes.

Robustness: The hash property to remain unchanged at non malicious attacks.

Non Malicious Attacks: Image conventional handling that changes the pixels but not the cognitive content.

Hash: The hash is a short binary string that summarizes the digital image content.

Collision Probability: The probability to obtain the same hash for two images with different cognitive content.

Randomness: The bits constituting the hash are independent.

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