Authentication and recovery of images using multiple watermarks

Chamlawi, Rafiullah; Khan, Asifullah; Usman, Imran

doi:10.1016/j.compeleceng.2009.12.003

Cited by 74 publications

(27 citation statements)

References 14 publications

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“…For semi-fragile self-recoverable watermarking, some popular schemes have been developed [3,4,11,15,21,28,33,43]. These schemes can be classified into two categories based on the methods and functionalities of embedded watermarks.…”

Section: Related Workmentioning

confidence: 99%

“…If a watermarked image suffers from modification, the self-recoverable watermarking scheme can localize the tampered region and recover the region by using hidden information in the image [3,4,9,11,12,14,15,18,19,21,22,27,28,31,33,42,43]. The self-recoverable fragile watermarking scheme does not need to tolerate content-preservation manipulations.…”

Section: Introductionmentioning

confidence: 99%

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Semi-fragile self-recoverable watermarking algorithm based on wavelet group quantization and double authentication

Zhang

Liu

et al. 2014

Multimed Tools Appl

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Semi-fragile self-recoverable watermarking algorithms are important to meet various requirements such as security, robustness, localization, and image recovery. However, current approaches are not adequate for this importance. Thus, we propose a novel semi-fragile and self-recoverable watermarking algorithm based on a group quantization and double authentication method. In the proposed algorithm, a target image is first split into 16×16 image blocks. For each image block, a five-bit authentication watermark is generated from the first-order statistical moment of the block and then is embedded into the mid-frequency band of another image block by a novel groupbased wavelet quantization method. With the generated watermarks, image security is enhanced by randomly permuting coefficients among a group and image robustness is improved by embedding the watermark in the largest coefficient inside a sub-group by significant difference parity quantization. The proposed double authentication ring structure effectively improves the image localization accuracy. Recovered image is a better approximate to the original image. Experimental comparisons of ours with other algorithms shows the effectiveness of the proposed self-recoverable and semi-fragile watermarking algorithm.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Semi-fragile self-recoverable watermarking algorithm based on wavelet group quantization and double authentication

Zhang

Liu

et al. 2014

Multimed Tools Appl

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“…Active authentication methods are further classified into two types digital watermarking and digital signatures [6][7][8]. Digital water marks are embedded into the images at the time of image acquisition or in processing stage and digital signatures embed some secondary information, usually extracted from image, at the acquisition end into the image .A lot of work has been carried in both digital signatures [9][10][11][12][13] and digital watermarking [14][15][16][17][18]. The main drawback of these approaches remains that they are to be inserted into the images at the time of recording using special equipments thus prior information about image becomes indispensable.…”

Section: Active Authenticationmentioning

confidence: 99%

Digital Image Forgeries and Passive Image Authentication Techniques: A Survey

Mushtaq¹,

Mir²

2014

IJAST

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“…There are a variety of different methods for watermark embedding and data recovery, such as discrete cosine transform [10,11], multiple watermarks [12], and source-channel coding [13].…”

Section: Introductionmentioning

confidence: 99%

Parameterization of LSB in Self-Recovery Speech Watermarking Framework in Big Data Mining

Song

et al. 2017

Security and Communication Networks

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The privacy is a major concern in big data mining approach. In this paper, we propose a novel self-recovery speech watermarking framework with consideration of trustable communication in big data mining. In the framework, the watermark is the compressed version of the original speech. The watermark is embedded into the least significant bit (LSB) layers. At the receiver end, the watermark is used to detect the tampered area and recover the tampered speech. To fit the complexity of the scenes in big data infrastructures, the LSB is treated as a parameter. This work discusses the relationship between LSB and other parameters in terms of explicit mathematical formulations. Once the LSB layer has been chosen, the best choices of other parameters are then deduced using the exclusive method. Additionally, we observed that six LSB layers are the limit for watermark embedding when the total bit layers equaled sixteen. Experimental results indicated that when the LSB layers changed from six to three, the imperceptibility of watermark increased, while the quality of the recovered signal decreased accordingly. This result was a trade-off and different LSB layers should be chosen according to different application conditions in big data infrastructures.

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Authentication and recovery of images using multiple watermarks

Cited by 74 publications

References 14 publications

Semi-fragile self-recoverable watermarking algorithm based on wavelet group quantization and double authentication

Semi-fragile self-recoverable watermarking algorithm based on wavelet group quantization and double authentication

Digital Image Forgeries and Passive Image Authentication Techniques: A Survey

Parameterization of LSB in Self-Recovery Speech Watermarking Framework in Big Data Mining

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