Factors that affect the performance of the DCT-block based image watermarking algorithms

Author(s):  
M. Eyadat
2014 ◽  
Vol 4 (1-2) ◽  
Author(s):  
Thien Huynh-The ◽  
Thuong Le-Tien ◽  
Tuan Nguyen-Thanh

In the paper, a robust blind watermarking method is introduced for gray-scale images based on wavelet tree quantization with an adaptive threshold in the extraction. Every block of 2×2 coefficients of High-Low subbands of the Wavelet tranform are grouped in a block through the parent-child relationship of the wavelet tree. Every scrambled binary watermark bit is embedded into each block based on the difference value of two largest coefficients. The watermark is recovered by comparing the difference values in each block to an adaptive threshold. The accuracy of an extracted watermark depends on the threshold which is determined by minimizing the sum of weighted within-class variance. The performance of the proposed watermarking method is represented through experimental results under various types of attack such as, Histogram Equalization, Cropping, Low-pass Filtering, Gaussian noise, Salt & Pepper noise and JPEG compression. In additions, the proposed method is also compared to recent methods in the extraction performance.


Author(s):  
Xi Zhao ◽  
Anthony T.S. Ho

With the tremendous growth and use of digital cameras and video devices, the need to verify the collected digital content for law enforcement applications such as crime scene investigations and traffic violations, becomes paramount if they are to be used as evidence in courts. Semi-fragile watermarking has become increasingly important within the past few years as it can be used to verify the content of images by accurately localising the tampered area and tolerating some non-malicious manipulations. There have been a number of different transforms used for semi-fragile image watermarking. In this chapter, we present two novel transforms for semi-fragile watermarking, using the Slant transform (SLT) as a block-based algorithm and the wavelet-based contourlet transform (WBCT) as a non-block based algorithm. The proposed SLT is compared with existing DCT and PST semi-fragile watermarking schemes. Experimental results using standard test images and simulated law enforcement images indicate that the SLT is more accurate for copy and paste attacks with non-malicious manipulations, such as additive Gaussian noise. For the proposed WBCT method, watermarking embedding is performed by modulating the parent-children relationship in the contourlet domain. Again, experimental results using the same test images have demonstrated that our proposed WBCT method achieves good performances in localising the tampered regions, even when the image has been subjected to non-malicious manipulations such as JPEG/JPEG2000 compressions, Gaussian noise, Gaussian filtering, and contrast stretching. The average miss detection rate is found to be approximately 1% while maintaining an average false alarm rate below 6.5%.


Optik ◽  
2016 ◽  
Vol 127 (4) ◽  
pp. 2374-2381 ◽  
Author(s):  
Hanaa A. Abdallah ◽  
Osama S. Faragallah ◽  
Hala S. Elsayed ◽  
Mohiy M. hadhoud ◽  
Abdalhameed A. Shaalan ◽  
...  

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
R. Eswaraiah ◽  
E. Sreenivasa Reddy

In telemedicine while transferring medical images tampers may be introduced. Before making any diagnostic decisions, the integrity of region of interest (ROI) of the received medical image must be verified to avoid misdiagnosis. In this paper, we propose a novel fragile block based medical image watermarking technique to avoid embedding distortion inside ROI, verify integrity of ROI, detect accurately the tampered blocks inside ROI, and recover the original ROI with zero loss. In this proposed method, the medical image is segmented into three sets of pixels: ROI pixels, region of noninterest (RONI) pixels, and border pixels. Then, authentication data and information of ROI are embedded in border pixels. Recovery data of ROI is embedded into RONI. Results of experiments conducted on a number of medical images reveal that the proposed method produces high quality watermarked medical images, identifies the presence of tampers inside ROI with 100% accuracy, and recovers the original ROI without any loss.


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