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In this paper, we present a novel multi-threaded parallel permutation and channel-combined diffusion for image encryption which is independent of plain text. In our proposed method, the coupled map lattice is used to generate the key sequences for multi-thread permutation and diffusion. Then intra- and inter-thread permutations are achieved using multi-threading in combination with the tent mapping. For the subsequent diffusion, this paper introduces a method based on channel-combined diffusing which simultaneously diffuses three channels. Experimental results indicate a high encryption performance with the capability of effectively resisting the known plain text and differential attacks. Our proposed method also has a lower computational complexity which enables its applicability in practical scenarios.

In this paper, a color image encryption method using the memristive hyperchaotic system and deoxyribonucleic acid (DNA) encryption is proposed. First, the pseudo-random sequences are generated by a keystream generation mechanism based on a memristive hyperchaotic system and the plain image. Due to this, the memristive hyperchaotic system has a complex dynamical behavior and is highly sensitive to initial conditions, the proposed keystream generation mechanism is highly random which is also dependent on the plain images. Second, a permutation based on the cycle-shift operation is designed to eliminate the correlations between adjacent pixels in the plain images. Then, the scrambled sequences are processed by DNA encryption to increase the system ability to defense the brute force attacks. Finally, the cipher image is obtained after the diffusion and interaction among red, green and blue components. Experimental analysis and performance comparisons show that the proposed method has high security, good efficiency and strong robustness under different attacks.

This paper deals with color image simplification using levelings. This class of connected filters suppresses details but preserves the contours of the remaining structures or objects. As the notion of "color structure" is not trivial, the formulation of morphological operators for color images involves many open issues. The principle choice of a well-defined color space is crucial and it is proposed to work on a luminance/saturation/hue representation defined by the norm L₁. A family of morphological color operators is then introduced using the classical formulation with total orderings by means of lexicographic cascades. In this framework, a methodology for color image simplification is introduced, which takes advantage of a saturation-controlled combination of the chromatic and the achromatic (or the spectral and the spatio-geometric) components. More precisely, it is based on the application of a color leveling to each significant region, specifically adapted to the nature (chromatic/achromatic) of the region and which needs an initial image partition into the homogenous regions. Experimental results illustrate the performance of the new developed algorithms.

Paintings convey the composition and characteristics of artists; therefore, it is possible to feel the intended style of painting and emotion of each artist through their paintings. In general, basic elements that constitute traditional paintings are color, texture, and composition (formative elements constituting the paintings are color and shape); however, color is the most crucial element expressing the emotion of a painting. In particular, traditional colors manifest the color containing historicity of the era, so the color shown in painting images is considered a representative color of the culture to which the painting belongs. This study constructed a color emotional system by analyzing colors and rearranged color emotion adjectives based on color combination techniques and clustering algorithm proposed by Kobayashi as well as I.R.I HUE & TONE 120 System. Based on the embodied color emotion system, this study confirmed classified emotions of images by extracting and classifying emotions from traditional Korean painted images, focusing on traditional painted images of the late Joseon Dynasty. Moreover, it was possible to verify the cultural traits of the era through the classified emotion images.

The analysis of fractal patterns has grown during the past years, mainly due to the wide range of applications to diverse scientific areas where fractals have been explored. It turns out that the key tool to study the complexity of a given system is the Fractal Dimension (FD), since this is its main invariant which throws quite useful information about the complexity that it presents when being examined with enough level of detail. In the proposed method, we adopt a hyper-surface partition method which considers the hyper-surface as continuous and divides the image into non-overlapped blocks. We present a novel counting method in the RGB color domain. The experimental results demonstrate that the proposed method shows its robustness and it can be performed as a reliable FD estimation approach for the color images. The running time of the proposed method is much shorter than that of other algorithms.

Although image retrieval for e-commerce field has a huge commercial potential, e-commerce oriented content-based image retrieval is still very raw. Modern online shopping systems have certain limitations. In particular, they use conventional tag-based retrieval and lack making use of visual content. The paper presents a methodology to retrieve images of shopping items based on fuzzy dominant colors. People regard color as an aesthetic issue, especially when it comes to choosing the colors of their clothing, apartment design and other objects around. No doubt, color inuences purchasing behavior — to a certain extent, it is a reection of human's likes and dislikes. The fuzzy color model that we are proposing represents the collection of fuzzy sets, providing the conceptual quantization of crisp HSI space having soft boundaries. The proposed method has two parts: assigning a fuzzy colorimetric profile to the image and processing the user query. We also use underlying mechanisms of attention from a theory of visual attention, like perceptual categorization. Subjectivity and sensitivity of humans in color perception and bridging the semantic gap between low-level color visual features and high-level concepts are major issues that we plan to tackle in this research.

A quaternion model for describing color image is proposed in order to evaluate its quality. Local variance distribution of luminance layer is calculated. Color information is taken into account by using quaternion matrix. The description method is a combination of luminance layer and color information. The angle between the singular value feature vectors of the quaternion matrices corresponding to the reference image and the distorted image is used to measure the structural similarity of the two color images. When the reference image and distorted images are of unequal size it can also assess their quality. Results from experiments show that the proposed method is better consistent with the human visual characteristics than MSE, PSNR and MSSIM. The resized distorted images can also be assessed rationally by this method.

Reversible watermarking methods are used for copyright protection and are able to recover the host image without distortion. Robust reversible watermarking technique should resist against intentional and unintentional image processing attacks. Robust reversible watermarking techniques should have three features namely imperceptibility, reversibility and robustness. In this paper, it is proposed to develop a new robust reversible blind watermarking for color images based on histogram construction of the wavelet coefficients constructed from the cover image. In the proposed approach, the red component of a host color image is decomposed into wavelet coefficients. Motivated by the excellent spatio-frequency localization properties of wavelets, this technique is proposed in the wavelet domain. The pixels are adjusted before watermark embedding such that both overflow and underflow of pixels during embedding is avoided and image is recovered without distortion. Based on histogram construction and the local sensitivity of Human Visual System (HVS) in wavelet domain, the watermark is embedded. For watermark extraction without host image, k-means clustering algorithm is proposed. The experimental results show that the proposed technique has good performance in terms of reversibility and robustness with the high quality of the watermarked image. The PSNR value of the recovered image is around 48dB which proves that the quality of the recovered image is not degraded.

Nowadays, digital watermarking is employed for authentication and copyright protection. In this paper, a secure image watermarking scheme based on lifting wavelet transform (LWT) and singular value decomposition (SVD), is proposed. Both LWT and SVD are used as mathematical tools for embedding watermark in the host image. In this work, the watermark is a speech signal which is segmented into shorted portions having the same length. This length is equal to 256 and these different portions constitute the different columns of a speech image. The latter is then embedded into a grayscale or color image (the host image). This procedure is performed in order to insert into an image a confidential data which is in our case a speech signal. But instead of embedding this speech signal directly into the image, we transform it into a matrix and treated it as an image (“a speech image”). Of course, this speech signal transformation permits us to use LWT-2D and SVD to both the host image and the watermark (“a speech image”). The proposed technique is applied to a number of grayscale and color images. The obtained results from peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) computations show the performance of the proposed technique. Experimental evaluation also shows that the proposed scheme is able to withstand a number of attacks such as JPEG compression, mean and median attacks. In our evaluation of the proposed technique, we used another technique of secure image watermarking based on DWT-2D and SVD.

Smartphones and tablets present data and information in color images. Due to factors such as yellowing pigmentation and miosis filter, elderly people may experience difficulties and confusion when looking at the color images on smartphones and tablets. In this paper, we propose a color enhancement method to improve the color perceived by elderly people. This method is based on the color perception of the elderly simulated using the uniform yellowing pigmentation method. The proposed method enhances the colors of the images to compensate for the effect of yellowing pigmentation and miosis filter. This is achieved by utilizing the error parameters between the original colors and colors perceived by the elderly. Implementing an adaptation matrix, the error parameters are modified and distributed back into the original colors iteratively. Experimental results showed that the proposed method improves the colors perceived by the elderly.

Digital watermarks have been embedded invisibly in digital media to protect copyrights of legal owners. In this paper two new robust digital color image watermarking schemes using fan beam projections are proposed and their imperceptibility, capacity and robustness are analyzed. The approach FBWLC adds a binary watermark to both the luminance and chrominance content of a color image whereas FBWC adds the watermark to the chrominance content of the color image and is based on Fan Beam Transform that takes multiple projections of the image from different angles. It is observed that FBWC scheme is robust to almost all the attacks and FBWLC scheme is more robust and guarantees zero bit error rate (BER) to most of the attacks on color images namely compression, filtering, blurring and sharpening and is compared with an existing approach based on Spatio Chromatic Discrete Fourier Transform (SCDFT). Also, when compared with other works in color image watermarking, these approaches embed a huge amount of data thereby increasing the watermarking capacity while preserving image quality by subjective evaluation.

The intensity gradient-based methods are commonly used in edge detection of images. However, these methods are not very suitable for color images and they change the shapes of object contours in large scales. In this paper, a novel density gradient-based method is proposed to solve these problems. The proposed method locates the edges using the density gradients of image pixels instead of the color/intensity gradients. Comparing with the traditional methods, the proposed approach can be applied more effectively to all types of images: gray level, color and multispectral images; and the detection results are invariant to the detection scales as well. It may find wide applications in computer vision and image processing.

The use of adaptive characteristics of SIFT, image features, the implementation of the write, erase operations on Extraction and color image hidden watermarking. From the experimental results, this algorithm has better imperceptibility and at the same time, is robust against geometric attacks and common signal processing.