scholarly journals A Blind Print-Recapture Robust Watermark Scheme by Calculating Self-Convolution

2019 ◽  
Vol 11 (4) ◽  
pp. 28-49 ◽  
Author(s):  
Mengmeng Zhang ◽  
Rongrong Ni ◽  
Yao Zhao
Keyword(s):  
Detection Rate ◽  
Color Image ◽  
Correlation Coefficients ◽  
Color Images ◽  
Geometric Transformation ◽  
Original Image ◽  
Color Spaces ◽  
Watermark Scheme ◽  
Robust Watermark ◽  
Cie Lab

A blind print-recapture robust watermark scheme is proposed. Watermark patterns are embedded into the space domain of a color image and can be detected from a print-recaptured version of the image without knowledge of the original image. The process of embedding invisible watermarks to convert RGB color images to CIE Lab color spaces and embed periodic watermarks in both color channels at the same time. Watermark extraction is achieved by calculating self-convolution and inverting the geometric transformation such as rotation and scale. Normalized correlation coefficients between the extracted and the embedded watermark pattern is calculated to determine whether there is watermark. The decision about the presence/absence of the watermark pattern is then determined by a threshold which is set 0.13, and the detection rate of 241 pictures is about 0.79.

A Reversible Watermarking Algorithm Resistant to Image Geometric Transformation

2019 ◽  
Vol 11 (1) ◽  
pp. 100-113
Author(s):  
Jian Li ◽  
Jinwei Wang ◽  
Shuang Yu ◽  
Xiangyang Luo
Keyword(s):  
High Performance ◽  
Side Information ◽  
Jpeg Compression ◽  
Reversible Watermarking ◽  
Experimental Results ◽  
Geometric Transformation ◽  
Original Image ◽  
Robust Watermark ◽  
Watermark Embedding ◽  
Watermarking Scheme

This article proposes a novel robust reversible watermarking algorithm. The proposed watermarking scheme is reversible because the original image can be recovered after extracting watermarks from the watermarked image, as long as it is not processed by an attacker. The scheme is robust because watermarks can still be extracted from watermarked images, even if it is undergone some malicious or normal operations like rotation and JPEG compression. It first selects two circles, which are centred at the centroid and the centre of image. Then, statistic quantities of these two circles are employed for robust watermark embedding by altering the pixels' value. The side information generated by above embedding process will be embedded as fragile watermarks at another stage to ensure the recovery of original image. Experimental results verify the high performance of the proposed algorithm in resisting various attacks, including JPEG compression and geometric transformation.

Analysis of SSIM Based Quality Assessment across Color Channels of Images

2015 ◽  
pp. 1233-1245
Author(s):  
T. Chandrakanth ◽  
B. Sandhya
Keyword(s):  
Image Processing ◽  
Quality Assessment ◽  
Color Space ◽  
Similarity Index ◽  
Human Perception ◽  
Structural Similarity ◽  
Subjective Assessment ◽  
Color Images ◽  
Color Spaces ◽  
Cie Lab

Advances in imaging and computing hardware have led to an explosion in the use of color images in image processing, graphics and computer vision applications across various domains such as medical imaging, satellite imagery, document analysis and biometrics to name a few. However, these images are subjected to a wide variety of distortions during its acquisition, subsequent compression, transmission, processing and then reproduction, which degrade their visual quality. Hence objective quality assessment of color images has emerged as one of the essential operations in image processing. During the last two decades, efforts have been put to design such an image quality metric which can be calculated simply but can accurately reflect subjective quality of human perception. In this paper, the authors evaluated the quality assessment of color images using SSIM (structural similarity index) metric across various color spaces. They experimented to study the effect of color spaces in metric based and distance based quality assessment. The authors proposed a metric using CIE Lab color space and SSIM, which has better correlation to the subjective assessment in a benchmark dataset.

scholarly journals A Reversible Watermarking System for Medical Color Images: Balancing Capacity, Imperceptibility, and Robustness

Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1024
Author(s):  
Xiaoyi Zhou ◽  
Yue Ma ◽  
Qingquan Zhang ◽  
Mazin Abed Mohammed ◽  
Robertas Damaševičius
Keyword(s):  
Color Image ◽  
Medical Images ◽  
Image Watermarking ◽  
Reversible Watermarking ◽  
Color Images ◽  
Discrete Wavelet ◽  
Original Image ◽  
Robust Solution ◽  
Geometric Attacks ◽  
Remote Healthcare

The authenticity and integrity of medical images in telemedicine has to be protected. Robust reversible watermarking (RRW) algorithms provide copyright protection and the original images can be recovered at the receiver’s end. However, the existing algorithms have limitations in their ability to balance the tradeoff among robustness, imperceptibility, and embedded capacity. Some of them are even not completely reversible. Besides, most medical image watermarking algorithms are not designed for color images. To improve their performance in protecting medical color image information, we propose a novel RRW scheme based on the discrete wavelet transform (DWT). First, the DWT provides a robust solution. Second, the modification of the wavelet domain coefficient guarantees the changes of integer values in the spatial domain and ensures the reversibility of the watermarking scheme. Third, the embedding scheme makes full use of the characteristics of the original image and watermarking. This reduces the modification of the original image and ensures better imperceptibility. Lastly, the selection of the Zernike moments order for geometric correction is optimized to predict attack parameters more accurately by using less information. This enhances the robustness of the proposed scheme against geometric attacks such as rotation and scaling. The proposed scheme is robust against common and geometric attacks and has a high embedding capacity without obvious distortion of the image. The paper contributes towards improving the security of medical images in remote healthcare.

scholarly journals An Efficient Noise Separation Technique for Removal of Gaussian and Mixed Noises in Monochrome and Color Images

2019 ◽  
Vol 8 (9S2) ◽  
pp. 588-601 ◽  
Keyword(s):  
Image Processing ◽  
Comparative Analysis ◽  
Image Quality ◽  
Image Quality Assessment ◽  
Color Image ◽  
Color Images ◽  
Original Image ◽  
High Quality ◽  
Noise Models ◽  
Single Approach

Images are often affected by different kinds of noise while acquiring, storing and transmitting it. Even the datasets gathered by the various image acquiring devices would be contaminated by noise. Hence, there is a need for noise reduction in the image, often called Image De-noising and thereby it becomes the significant concerns and fundamental step in the area of image processing. During image de-noising, the big challenge before the researchers is removing noise from the original image in such a way that most significant properties like edges, lines, etc., of the image, should be preserved. There were various published algorithms and techniques to de-noise the image and every single approach has its own limitations, benefits, and assumptions. This paper reviews the noise models and presents a comparative analysis of various de-noising filters that works for color images with single and mixed noises. It also suggests the best filter for color that involve in producing a high-quality color image. The metrics like PSNR, Entropy, SSIM, MSE, FSIM, and EPI are considered as image quality assessment metric

scholarly journals Tamper Detection in Color Image

2008 ◽  
Vol 5 (1) ◽  
pp. 155-159
Author(s):  
Baghdad Science Journal
Keyword(s):  
Color Image ◽  
Spatial Domain ◽  
Tamper Detection ◽  
Color Images ◽  
Fragile Watermarking ◽  
Original Image ◽  
Digital Color Images ◽  
Watermarking Scheme

In this work a fragile watermarking scheme is presented. This scheme is applied to digital color images in spatial domain. The image is divided into blocks, and each block has its authentication mark embedded in it, we would be able to insure which parts of the image are authentic and which parts have been modified. This authentication carries out without need to exist the original image. The results show the quality of the watermarked image is remaining very good and the watermark survived some type of unintended modification such as familiar compression software like WINRAR and ZIP

scholarly journals Testing the randomness of shares in color visual cryptography

2021 ◽  
Author(s):  
Leszek J. Chmielewski ◽  
Mariusz Nieniewski ◽  
Arkadiusz Orłowski
Keyword(s):  
Color Image ◽  
Visual Cryptography ◽  
Color Images ◽  
Reconstructed Image ◽  
Original Image ◽  
Numerical Processing ◽  
Human Eye ◽  
Black And White ◽  
Randomness Tests

AbstractThe concept of black-and-white visual cryptography with two truly random shares, previously applied to color images, was improved by mixing the contents of the segments of each coding image and by randomly changing a specified number of black pixels into color ones. This was done in such a way that the changes of the contents of the decoded image were as small as possible. These modifications made the numbers of color pixels in the shares close to balanced, which potentially made it possible for the shares to be truly random. The true randomness was understood as that the data pass the suitably designed randomness tests. The randomness of the shares was tested with the NIST randomness tests. Part of the tests passed successfully, while some failed. The target of coding a color image in truly random shares was approached, but not yet reached. In visual cryptography, the decoding with the unarmed human eye is of primary importance, but besides this, simple numerical processing of the decoded image makes it possible to greatly improve the quality of the reconstructed image, so that it becomes close to that of the dithered original image.

Analysis of SSIM based Quality Assessment across Color Channels of Images

2015 ◽  
Vol 4 (3) ◽  
pp. 30-42 ◽  
Author(s):  
T. Chandrakanth ◽  
B. Sandhya
Keyword(s):  
Image Processing ◽  
Quality Assessment ◽  
Color Space ◽  
Similarity Index ◽  
Human Perception ◽  
Structural Similarity ◽  
Subjective Assessment ◽  
Color Images ◽  
Color Spaces ◽  
Cie Lab

Advances in imaging and computing hardware have led to an explosion in the use of color images in image processing, graphics and computer vision applications across various domains such as medical imaging, satellite imagery, document analysis and biometrics to name a few. However, these images are subjected to a wide variety of distortions during its acquisition, subsequent compression, transmission, processing and then reproduction, which degrade their visual quality. Hence objective quality assessment of color images has emerged as one of the essential operations in image processing. During the last two decades, efforts have been put to design such an image quality metric which can be calculated simply but can accurately reflect subjective quality of human perception. In this paper, the authors evaluated the quality assessment of color images using SSIM (structural similarity index) metric across various color spaces. They experimented to study the effect of color spaces in metric based and distance based quality assessment. The authors proposed a metric using CIE Lab color space and SSIM, which has better correlation to the subjective assessment in a benchmark dataset.

Study on Correlation of Color Components Image in Different Color Spaces

2012 ◽  
Vol 262 ◽  
pp. 86-91
Author(s):  
Yang Jin ◽  
Zhen Liu ◽  
Peng Fei Wang ◽  
San Guo Liu ◽  
Hong Jie Zhai
Keyword(s):  
Cross Correlation ◽  
Color Image ◽  
Color Space ◽  
Correlation Coefficients ◽  
Color Spaces ◽  
Color Component ◽  
Cross Correlations ◽  
The Difference ◽  
Opposite Color ◽  
Color Components

Color image is an information substance with color components, among which exists correlation. In order to investigate the internal relevance of information in color image and to find out the dependence between them, to research the correlation of the color component image is significant. In order to investigate the relationship between the color space and the correlation of the component images, color spaces RGB/ LCH/ LAB/ OHTA/ YCC are selected and the correlation coefficients and cross correlations of the component images are computed and analyzed on MATLAB platform. The Result shows, that the statistical correlation coefficients of component images under RGB color space are the highest, while in OHTA color space the lowest are showed. The correlation coefficients under LAB and LCH are relative lower. In the opposite color spaces, the correlation coefficients of two opposite color components images are higher than the coefficients between the lightness and one of the opposite color component images. For the cross correlation of color component images, it shows a weak negative exponent relationship between pixel distance and cross correlation. The average cross correlation of component images in LCH space is obvious lower than in other spaces, while the levels of cross correlation in other spaces are similar. The relationship between cross correlation and color characteristics of image in RGB color space is closely, while in OHTA space, the difference of cross correlations among component images are usually small. In LCH space, the difference of cross correlations among component images is obvious, the cross correlation among chroma and the other components (lightness and hue) are much lower.

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