Protecting Digital Images Using DTCWT-DCT

Ramani, Karthik; Prasad, E. V.; Varadarajan, S.

doi:10.1007/978-3-642-15766-0_6

Cited by 5 publications

(17 citation statements)

References 8 publications

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“…The new proposed fingerprint image watermarking algorithm is extended from combining the idea of K. Ramani et al [10] and Benoraira et al [12], that uses the hybrid domain of DTCWT and DCT, with the differential embedding method. The technique of differential embedding depends on two DCT transformed sub-vectors to ensure the blind extraction of the watermark.…”

Section: Methodology: Dtcwt-dctmentioning

confidence: 99%

“…The proposed method is achieved under the biometric image (fingerprint), which means that it concentrates on biometric features. These features are combined between unique ridges and minutia points for the purpose of improving the security of biometric data, whilst the proposed method by Ramani et al [10] concentrated on the copyright protection of digital images. In addition, it was based on the differential method to choose the best place of the embedded watermark without affecting minutia points within the cover fingerprint image.…”

Section: Methodology: Dtcwt-dctmentioning

confidence: 99%

“…Furthermore, achieving the blindness means that there is no needed for the original cover image to extract the embedded watermark. While, K. Ramani et al [10] did not mention this method (differential method) in his algorithm. On the other hand, the choice of the embedding of the coefficient sub-bands in the proposed DCT-DTCWT algorithm is far more adjustable than those used in the study of Benoraira et al [12] (the used frequency domain is not the same) because of the proprieties of the used transform domain.…”

Section: Methodology: Dtcwt-dctmentioning

confidence: 99%

“…In the multiresolution domain, DWT has become the most advanced choice among all the multiresolution domains for image watermarking techniques. This is because the magnitude of DWT coefficients is larger in the lowest band at each level of decomposition; it is possible to use a larger scaling factor for watermark embedding [10]. In addition, DWT is very suitable to identify the areas in the host image where a watermark can be embedded effectively.…”

Section: Related Workmentioning

confidence: 99%

“…On the other hand, to evaluate the performance of the proposed DTCWT-DCT method, we have implemented the proposed watermarking algorithm on the standard image used in [10], "lena", as a cover image with a size of 512x512, and the sequence binary with a size of 1000 bit, as a the watermark data. The robustness against different types of attacks is compared based on PSNR value and normalized cross correlation values (NCC).…”

Section: B Robustness Testsmentioning

confidence: 99%

See 4 more Smart Citations

Robust Blind Watermarking Technique Against Geometric Attacks for Fingerprint Image Using DTCWT-DCT

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Awang

Benziane

2020

eijs

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In this research paper, a new blind and robust fingerprint image watermarking scheme based on a combination of dual-tree complex wavelet transform (DTCWT) and discrete cosine transform (DCT) domains is demonstrated. The major concern is to afford a solution in reducing the consequence of geometric attacks. It is due to the fingerprint features that may be impacted by the incorporated watermark, fingerprint rotations, and displacements that result in multiple feature sets. To integrate the bits of the watermark sequence into a differential process, two DCT-transformed sub-vectors are implemented. The initial sub-vectors were obtained by sub-sampling in the host fingerprint image of both real and imaginary parts of the DTCWT wavelet coefficients. The basic difference between the relevant sub-vectors of the watermarked fingerprint image in the extraction stage directly provides the inserted watermark sequence. It is not necessary to extract watermark data from an original fingerprint image. Therefore, the technique suggested is evaluated using 80 fingerprint images from 10 persons, from both CASIA-V5-DB and FVC2002-DB2 fingerprint database. For each person, eight fingerprints are set as the template and the watermark are inserted in each image. A comparison between the obtained results with other geometric robust techniques results is performed afterwards. The comparison results show that the proposed technique has stronger robustness against common image processing processes and geometric attacks such as cropping, resizing, and rotation.

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Section: Methodology: Dtcwt-dctmentioning

confidence: 99%

Section: Methodology: Dtcwt-dctmentioning

confidence: 99%