基于DCT特征点的感知图像Hash函数

Abstract

Abstract: This paper proposes a perceptual image hash function using discrete cosine transform (DCT) based feature points.Specifically,the input image is first mapped to a normalized image by preprocessing.The normalized image is then divided into non-overlapping blocks.Next,two dimensional DCT is applied toeach block,and AC coefficients of each block are used to form a feature point.Finally,gravity center of the feature points is calculated and the hash is obtained by computing the Euclidian distance between the gravity center and each feature point.Experiments show that the proposed algorithm is robust against normal digital operations and reaches good discrimination.Receiver operating characteristics (ROC) curve comparisons indicate that the proposed algorithm outperforms three well-known existing algorithms.

Key words: Image hash, hash function, image retrieval, copy detection, receiver operating characteristics (ROC)

CLC Number:

TP391.411

TANG Zhen-jun, DAI Yu-min, ZHANG Xian-quan, ZHANG Shi-chao. Perceptual Image Hash Function Using DCT-Based Feature Points[J].Journal of Guangxi Normal University(Natural Science Edition), 2012, 30(3): 135-141.

References

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Perceptual Image Hash Function Using DCT-Based Feature Points

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