Robust image hash in Radon transform domain for authentication

Lei, Yanqiang; Wang, Yuan‐Gen; Huang, Jiwu

doi:10.1016/j.image.2011.04.007

Cited by 101 publications

(60 citation statements)

References 25 publications

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“…One of the major disadvantages of watermarking is that it will deform the content. Some of the existing methods [1]- [7] uses hash signature based methods. In these methods, a hash code is entrenched with the image before transmission.…”

Section: Related Workmentioning

confidence: 99%

Proficient Hash Sensitivity Growth for Optimized Image Forgery Detection

Anitha¹,

Bose²

2014

IJCATR

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Abstract:The motive behind the work is to provide an effective solution to the most sensitive issue called image forgery that is occurring due to increase in an availability of enormous image modification software. The image forgery causes drastic bad effects in the society such as copyright misuse, evident change in the court of law, quality control, medical image forgery, etc. There are numerous steps taken in order to detect forgery in images, but how far they are successful is the question here. In this paper, an advanced and efficient solution is provided for the forgery detection which can overcome the drawbacks of the existing works by accurately detecting the salient regions by considering both the local and global features of an image (when considering the whole image it is global and when considering only the specific part of an image it is local) and based on this a technique is proposed called hash sensitivity growth method (HSGM), which can accurately detect the salient regions of an image and extract feature contents from that region, hence provide efficient sensitivity growth to a hash, as the sensitivity of the hash is increased it can accurately detect even smaller area tampering and it is robust to normal image processing.

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Section: Related Workmentioning

confidence: 99%

Proficient Hash Sensitivity Growth for Optimized Image Forgery Detection

Anitha¹,

Bose²

2014

IJCATR

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“…However, since Fourier transform did not offer localized frequency information, this method was not able to detect malicious local modifications. In a more recent development, a perceptual image hashing scheme based Radon Transform is proposed in (Lei et al, 2011) where the authors perform Radon Transform on the image and calculate the moment features which are invariant to translation and scaling in the projection space. Then Discrete Fourier Transform (DFT) is applied on the moment features to resist rotation.…”

Section: Review Of Some Related Work On Perceptual Image Hashing Techmentioning

confidence: 99%

Perceptual Image Hashing

Hadmi¹,

Puech²,

Said³

et al. 2012

Watermarking - Volume 2

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“…The content of the image is represented as a small code called Hash code [1]. Hash code can be generated by extracting local and global features [2], Watermarking methods [3] [4], Transform co-efficient [5] [6], and much more. In recent work combining two or more hashed techniques to generate the hash code is also most common to take advantage of different hashing techniques [7].…”

Section: Introductionmentioning

confidence: 99%