Palette Images Research Articles

Invertible Secret Image Sharing with Authentication for Embedding Color Palette Image into True Color Image

Invertible Secret Image Sharing with Authentication for Embedding Color Palette Image into True Color Image

A Deep Learning Image-to-Image Translation Approach for a More Accessible Estimator of the Healing Time of Burns.

An accurate and timely diagnosis of burn severity is critical to ensure a positive outcome. Laser Doppler imaging (LDI) has become a very useful tool for this task. It measures the perfusion of the burn and estimates its potential healing time. LDIs generate a 6-color palette image, with each color representing a healing time. This technique has very high costs associated. In resource-limited areas, such as low- and middle-income countries or remote locations like space, where access to specialized burn care is inadequate, more affordable and portable tools are required. This study proposes a novel image-to-image translation approach to estimate burn healing times, using a digital image to approximate the LDI. This approach consists of a U-net architecture with a VGG-based encoder and applies the concept of ordinal classification. Paired digital and LDI images of burns were collected. The performance was evaluated with 10-fold cross-validation, mean absolute error (MAE), and color distribution differences between the ground truth and the estimated LDI. Results showed a satisfactory performance in terms of low MAE ( 0.2370 ±0.0086). However, the unbalanced distribution of colors in the data affects this performance. This novel and unique approach serves as a basis for developing more accessible support tools in the burn care environment in resource-limited areas.

Reversible Data Hiding in Palette Images

Reversible data hiding (RDH) has been investigated for over two decades. Depending on the application scenario, it can be divided into RDH and reversible data hiding in encrypted images (RDHEI). Interestingly, almost all studies on RDH/RDHEI have been conducted on gray-scale images, and relatively few studies have been conducted on color images compared to those on gray-scale images. Moreover, very few studies have been undertaken on palette images as a widely used image format. For palette images in which pixels are not gray-scale levels but color table indexes, it is difficult to apply traditional RDH/RDHEI methods directly. Therefore, we propose a new framework for RDH/RDHEI specifically for palette images. This framework adds a route selection algorithm before the conventional RDH/RDHEI approach. To be specific, we propose a method named the shortest route with correlation and frequency selection to reorder the color table, followed by a correlation reconstruction of the remapped index image according to this color table. The experimental results show the improvement brought by our proposed route selection to the existing RDH/RDHEI methods in palette images.

Comparison of image palette trimming techniques for segmentation task

This paper offers a comparison of palette quantization techniques for image segmentation task, raster image vectorization optimization purpose. Image color spaces are reviewed. The elaborated methods are characterized, their strong side and weaknesses are pointed out, the application advisability of listed methods are analyzed. Image segmentation is a highly demanded task in lots of areas requiring application of advanced algorithms both for shape recognition and color processing. Color quantization continues to be a subject of active research. The latest research is aimed at optimizing existing algorithms and finding new methodologies. The significant progress in the field of digital technologies in cooperation with artificial intelligence technologies solves old problems and raises new ones. The trade-off between computational efficiency and segmentation accuracy is still a key challenge, especially in real-time applications. In addition, the adaptation of these methods to various fields, such as medical industry, video assistants in sports, analysis of space images, surveillance systems, creates challenges for future research. Purpose: research of color quantization methods, their efficiency and applicability for image segmentation tasks solving.

Block-Based Steganography Method Using Optimal Selection to Reach High Efficiency and Capacity for Palette Images

The primary goal of steganographic methods is to develop statically undetectable methods with high steganographic capacity. The embedding efficiency is one kind of measure for undetectability. Block-based steganography methods have been proposed for achieving higher embedding efficiency under limited embedding capacity. However, in these methods, some blocks with larger embedding distortions are skipped, and a location map is usually incorporated into these methods to record the embedding status of each block. This reduces the embedding capacity for secret messages. In this study, we proposed a block-based steganography method without a location map for palette images. In this method, multiple secret bits can be embedded in a block by modifying at most one pixel with minimal embedding distortion; this enables each block to be used for data embedding; thus, our method provides higher embedding capacity. Furthermore, under the same capacity, the estimated and experimental embedding efficiencies of the proposed method are compared with those of Imaizumi et al. and Aryal et al.’s methods; the comparisons indicate that the proposed method has higher embedding efficiency than Imaizumi et al. and Aryal et al.’s methods.

A New Steganography Method for Dynamic GIF Images Based on Palette Sort

This paper proposes a new steganography method for hiding data into dynamic GIF (Graphics Interchange Format) images. When using the STC framework, we propose a new algorithm of cost assignment according to the characteristics of dynamic GIF images, including the image palette and the correlation of interframes. We also propose a payload allocation algorithm for different frames. First, we reorder the palette of GIF images to reduce the modifications on pixel values when modifying the index values. As the different modifications on index values would result in different impacts on pixel values, we assign the elements with less impact on pixel values with small embedding costs. Meanwhile, small embedding costs are also assigned for the elements in the regions that the interframe changes are large enough. Finally, we calculate an appropriate payload for each frame using the embedding probability obtained from the proposed distortion function. Experimental results show that the proposed method has a better security performance than state-of-the-art works.

Gender approach in the analysis of performing versions (on the example of F. Chopin’s Second Piano Concerto performed by E. Kissin, C. Arrau, Lang Lang, M. Argerich, B. Davidovich)

Gender approach in the analysis of performing versions (on the example of F. Chopin’s Second Piano Concerto performed by E. Kissin, C. Arrau, Lang Lang, M. Argerich, B. Davidovich)

Sharing and hiding a secret image in color palette images with authentication

Existing secret image sharing (SIS) schemes with steganography and authentication are only suitable for uncompressed grayscale images. To make it more practical, a scheme for sharing and hiding a secret image in color palette images with authentication is proposed in this paper. Three commonly used system color palettes are considered. In sharing phase, a secret image is encoded into shared bits by polynomial based SIS. The shared bits are concealed into the color palette cover image to form the stego images. Meanwhile, the authentication parity bits are generated and embedded as well. Two embedding strategies are developed for the color palette images. In authentication and recovery phase, the integrity of each stego image is verified. Then, the secret image are reconstructed by sufficient authentic stego images. Experimental results are demonstrated to show the effectiveness and merits of the proposed scheme.

A Multilayer Steganography Method with High Embedding Efficiency for Palette Images

A Multilayer Steganography Method with High Embedding Efficiency for Palette Images

Image steganography based on color palette transformation in color space

In this paper, we present a novel image steganography method which is based on color palette transformation in color space. Most of the existing image steganography methods modify separate image pixels, and random noise appears in the image. By proposing a method, which changes the color palette of the image (all pixels of the same color will be changed to the same color), we achieve a higher user perception. Presented comparison of stegoimage quality metrics with other image steganography methods proved the new method is one of the best according to Structural Similarity Index (SSIM) and Peak Signal Noise Ratio (PSNR) values. The capability is average among other methods, but our method has a bigger capacity among methods with better SSIM and PSNR values. The color and pixel capability can be increased by using standard or adaptive color palette images with smoothing, but it will increase the embedding identification possibility.

Dual Optimization of Monochrome Images Tone Approximation using Parallel Evolutionarily Genetic Search

The paper considers the optimization problem of tone approximation for monochrome (for example: in grayscale palette) images. The procedure of tone approximation implies the reduction of approximated image’s number of tones, which are used in image displaying, compared to number of tones in the original image. The point of the procedure optimization consists of minimization of visual quality loses that estimated according to total or mean deviation between the same pixels of original image and approximated one. As a tool of the optimization the hybrid algorithm is used. It was developed and investigated by authors. The hybrid algorithm combines heuristic and deterministic algorithms of searching the best structure of approximating palette according to criterion of deviations minimization. The heuristic algorithm is based on evolutionarily-genetic paradigm. The main goal of heuristic stage is the reduction of search area of approximating palette’s structures that are the closest to optimum. Such role for heuristic stage was defined according to its fast computational time. The goal of deterministic algorithm of directed exhaustive search is to find the nearest extreme for the result that was obtained by previous algorithm. The developed hybrid algorithm allows to provide dual optimization of tone approximation. It means that the algorithm provides a result, in which two different criteria become optimal relative to each other. The current investigation is devoted to consideration of possibility to increase the effectiveness of hybrid algorithm on the level of heuristic stage. The possibility of implementation the parallel model of evolutionarily-genetic algorithm with different settings is considered. The results of initial experiments are discussed and compared with known algorithm of tone approximation.

Encrypted separable reversible watermarking with authentication and error correction

Reversible Watermarking (RW) in encrypted images helps to reconstruct the original content and embedded data without distortion while protecting the owner’s privacy. The security and integrity of embedded data is very much demanding. In this paper, an efficient RW method is proposed that recovers the embedded data from the marked encrypted color palette images in the presence of attacks. In this method, embeddable color-triples are constructed by employing color partitioning. Next, the cryptographic SHA-256 hash and Bose–Chaudhuri–Hocquenghem (BCH) are applied over the secret information to ensure the authenticity and integrity. The hash authenticated secret data is embedded into the encrypted color palette image. The secret data is extracted using the separable color partitioning method and authenticated with cryptographic hash function. The proposed method has higher embedding capacity when compared to other relative schemes. The BCH codes helps to recover the secret data and cover image in the presence of noise and attacks.

“A WRITER — A NERVE CELL OF THE NATION”: SPECIFICITY OF THE AUTHOR’S NATIONAL SELF-IDENTITY IN THE “DIARIES” OF OLES GONCHAR

The article is devoted to researching of “Diaries” written by Oles Gonchar through the prism of the author’s national self-identity. The first diary entry is dated June, 1943 and the last entry dated July, 1995. The Ukrainian national features are found out to be revealing in a diary prose of Oles Gonchar both at the content and the form levels through the system of interrelated dominants; the signs of these specific dominants can be traced in the reflection of its characteristics in the writer’s chronological notes. The author of the paper has conducted an analysis of the main motives revealed in the diary entries being realized in the image palette, archetypes, place names — all these are combined with ethnic specificity. The author summarizes the writer’s ideological viewsthat identifiedthe genesis of popular perception of reality incorporating sincere apologetics of socialism in prewar time, romantic passion (enthusiasm) for European revolutionary ideas throughout losses, tragedies, frustrations and failures of war, gradual awareness of the essence of the Soviet power, Stalin’s bloody crimes against his own peopleas well as the genuine admiration for a short “Khrushchev Thaw” elimination of which in Brezhnev “stagnation period” convinced Gonchar in the necessity of democratization of society. The results of the conducted research determinesome factorssuch as: the Chernobyl disaster, degeneration of national spirituality, displacement of the Ukrainian language on the margins of being — all these key factorsmade Gonchar a leader of spiritual revival of Ukraine.

Separable Reversible Data Hiding for Encrypted Palette Images With Color Partitioning and Flipping Verification

Reversible data hiding (RDH) into encrypted images is of increasing attention to researchers as the original content can be perfectly reconstructed after the embedded data are extracted while the content owner’s privacy remains protected. The existing RDH techniques are designed for grayscale images and, therefore, cannot be directly applied to palette images. Since the pixel values in a palette image are not the actual color values, but rather the color indexes, RDH in encrypted palette images is more challenging than that designed for normal image formats. To the best knowledge of the authors, there is no suitable RDH scheme designed for encrypted palette images that has been reported, while palette images have been widely utilized. This has motivated us to design a reliable RDH scheme for encrypted palette images. The proposed method adopts a color partitioning method to use the palette colors to construct a certain number of embeddable color triples, whose indexes are self-embedded into the encrypted image so that a data hider can collect the usable color triples to embed the secret data. For a receiver, the embedded color triples can be determined by verifying a self-embedded check code that enables the receiver to retrieve the embedded data only with the data hiding key. Using the encryption key, the receiver can roughly reconstruct the image content. Experiments have shown that our proposed method has the property that the presented data extraction and image recovery are separable and reversible. Compared with the state-of-the-art works, our proposed method can provide a relatively high data-embedding payload, maintain high peak signal-to-noise ratio values of the decrypted and marked images, and have a low computational complexity.

Photo-id of blue whale by means of the dorsal fin using clustering algorithms and color local complexity estimation for mobile devices

We present an automatic program of blue whale photo-identification for mobile devices. The proposed technique works in the wavelet domain to reduce the image size and the processing time of the proposed algorithm, and with an edge enhancement filter, the characteristics of the blue whale are preserved. Additionally, an image palette reduction algorithm based on local image complexity estimation is introduced to eliminate redundant colors, thus decreasing the number of pixels that are bad classified in the segmentation process and minimizing the resource consumption of the mobile device. The segmented image is obtained with the FCM (fuzzy C-means) or K-means algorithms incorporating a dynamic filtering which is proposed in this paper to improve the brightness and contrast of the acquired image increasing the performance of the image segmentation. Experimental results show that the proposed approach potentially could provide a real-time solution to photo-id of blue whale images and it can be transportable and portable power for mobile devices. Finally, the proposed methodology is simple, efficient, and feasible for photo-id applications in mobile devices.

Image palette: painting style transfer via brushstroke control synthesis

As one kind of technology of style transfer, painting style transfer can be used to render the sample images with a specific art style. With this technology, we can render the target images in the same style as the samples after some computation. We present a new approach of painting style transfer in which such a style transfer artwork is done by simulating the process of creation. We take the sample as a palette where users can select arbitrary contours or textures as the input brush strokes. We then analyze the style feature of the brush strokes and use this feature for synthesis and style transfer along the stroke curves learned from the specified area in target images or target 3D models to get the same painting style as the samples. Based on this approach, we also design and realize the corresponding painting system. The results show that the users can get a style-transferred personalized target image just by using the given sample images with the least interactions.

Multi-layer assignment steganography using graph-theoretic approach

This paper proposes a novel multibit assignment steganographic scheme for palette images, in which some colors in the palette are exploited to represent several secret bits. For the proposed scheme, each palette color is treated as a graph vertex, and an edge among any two vertices indicates an adjacent relationship between them. A graph traversal technique named depth-first search is used to accomplish the multibit assignment for the vertices that correspond to the palette colors. The major idea of the proposed data-embedding is to modify colors of image pixels according to the assigned bits and secret message. Image pixels are classified as embeddable pixels and non-embeddable pixels before data-embedding. During the data-embedding, for each embeddable pixel, if the original color of the pixel matches the secret data, the pixel is then kept unchanged; otherwise, a suitable adjacent color of the original color will be used to replace the original color so that the new color matches the secret data. Experimental results show that the secret data can be embedded and extracted successfully without introducing visual artifacts, and the proposed scheme can always achieve a high capacity or maintain good image quality, comparing with the related works.

The system to analyze of stability of robust steganographic algorithms

When building steganographic system for copyright protection, two requirements are presented to the algorithms. First of all, robustness requirement is presented: the resistance level of the data embedded into image to intentional or unintentional container distortion. Second, the requirement of minimal visible container changes when embedding data into an image. These requirements contradict one another; this is due to the fact that the smaller is value of distortion included into image while information imbedding, the less built-in data capability will be. Almost all the algorithms proposed allow to vary resistance parameters and the amount of included changes by changing a so-called embedding force coefficient P. Besides this, the data capability depends on format, size, and image palette, as well as on types and degree of distortion (attacks), to which the image may be exposed. Therefore, a compromise is needed between these two parameters for constructing a reliable and effective steganographic system.This paper describes the software solution developed for a practical evaluation of the stability of steganographic methods for hiding information in digital images.The results received allow us, when creating the system of steganographic data embedding into digital images, to reasonably choose the most appropriate methods and parameters of algorithms that provide the needed capability level to certain container distortions simultaneously with possible "invisibility" of embedded messages. Implementation of the most appropriate methods and parameters of algorithm obtained with the help of system developed into information security area will improve the existing steganographic systems efficiency.

Context Coding of Depth Map Images Under the Piecewise-Constant Image Model Representation

This paper introduces an efficient method for lossless compression of depth map images, using the representation of a depth image in terms of three entities: 1) the crack-edges; 2) the constant depth regions enclosed by them; and 3) the depth value over each region. The starting representation is identical with that used in a very efficient coder for palette images, the piecewise-constant image model coding, but the techniques used for coding the elements of the representation are more advanced and especially suitable for the type of redundancy present in depth images. Initially, the vertical and horizontal crack-edges separating the constant depth regions are transmitted by 2D context coding using optimally pruned context trees. Both the encoder and decoder can reconstruct the regions of constant depth from the transmitted crack-edge image. The depth value in a given region is encoded using the depth values of the neighboring regions already encoded, exploiting the natural smoothness of the depth variation, and the mutual exclusiveness of the values in neighboring regions. The encoding method is suitable for lossless compression of depth images, obtaining compression of about 10-65 times, and additionally can be used as the entropy coding stage for lossy depth compression.

Robust Data Hiding Method for Palette Images Using Double Messages Embedding

The commonly used JPEG and GIF images on Internet web sites have become more popular for steganographic applications. However, the use of lossy image compression will destroy the embedded message on the marked images. This article presents a novel data hiding method for palette images which can embed double messages, secret and robust messages, into palette images. The receivers can extract both the embedded two messages with no loss if the stego-image is not encountered any attack. If the stego-image is attacked, we can still extract the robust message with little distortion from the attacked images. The proposed method is based on parity check and statistical quantity histogram. Experiment results show the proposed method can achieve high performance in embedding capacity and robustness.