Robust Image Hashing for Detecting Small Tampering Using a Hyperrectangular Region

In order to improve the sensitive to illegal manipulations of image hashing, a novel robust image hashing algorithm based on fractional Fourier transform (FRFT) for detecting and localizing image tampering is proposed in this paper. The framework of generating an image hashing includes three steps: preprocessing, feature extracting and post processing. The robust hashing sequence is obtained by FRFT coefficients of image blocks. The security of proposed algorithm is totally depended on the orders of FRFT which are saved as secret keys. Experimental results show that the proposed scheme is robust against perceptually acceptable modifications to the image such as JPEG compression, mid-filtering, and rotation, more importantly the tampered place can be identified accurately.

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Robust Image Hashing Using Radon Transform and Invariant Features

Radioengineering ◽

10.13164/re.2016.0556 ◽

2016 ◽

Vol 25 (3) ◽

pp. 556-564 ◽

Cited By ~ 3

Author(s):

Y. L. Liu ◽

G. J. Xin ◽

Y. Xiao

Keyword(s):

Radon Transform ◽

Image Hashing ◽

Invariant Features ◽

Robust Image ◽

Robust Image Hashing

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A Secure and Robust Image Hashing Scheme Using Gaussian Pyramids

Entropy ◽

10.3390/e21111132 ◽

2019 ◽

Vol 21 (11) ◽

pp. 1132 ◽

Cited By ~ 4

Author(s):

Iram Bashir ◽

Fawad Ahmed ◽

Jawad Ahmad ◽

Wadii Boulila ◽

Nouf Alharbi

Keyword(s):

False Negative ◽

Hash Functions ◽

Feature Space ◽

Image Hashing ◽

Gaussian Pyramid ◽

Image Hash ◽

Perceptual Hash ◽

Robust Image ◽

Robust Image Hashing ◽

Cryptographic Hash Functions

Image hash is an alternative to cryptographic hash functions for checking integrity of digital images. Compared to cryptographic hash functions, an image hash or a Perceptual Hash Function (PHF) is resilient to content preserving distortions and sensitive to malicious tampering. In this paper, a robust and secure image hashing technique using a Gaussian pyramid is proposed. A Gaussian pyramid decomposes an image into different resolution levels which can be utilized to obtain robust and compact hash features. These stable features have been utilized in the proposed work to construct a secure and robust image hash. The proposed scheme uses Laplacian of Gaussian (LOG) and disk filters to filter the low-resolution Gaussian decomposed image. The filtered images are then subtracted and their difference is used as a hash. To make the hash secure, a key is introduced before feature extraction, thus making the entire feature space random. The proposed hashing scheme has been evaluated through a number of experiments involving cases of non-malicious distortions and malicious tampering. Experimental results reveal that the proposed hashing scheme is robust against non-malicious distortions and is sensitive to detect minute malicious tampering. Moreover, False Positive Probability (FPP) and False Negative Probability (FNP) results demonstrate the effectiveness of the proposed scheme when compared to state-of-the-art image hashing algorithms proposed in the literature.

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