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Transferring data through unsecured communication channels exposes it to the risk of sabotage and theft by unauthorized persons. Therefore, secure and modern methods must be provided to protect this data upon transmission. This study suggests a new way to use deoxyribonucleic acid (DNA) coding and chaotic maps to create two security levels for data protection. The first level includes generating a key using a one-dimensional logistic map and then converting the values to DNA codes. In contrast, the image color data is converted to DNA codes. After that, the XOR operation is applied between key and color codes by using four rules (2, 4, 6, and 8) from the encoding DNA rules. The second level includes generating three keys via a three-dimensional logistic map. After that, an XOR operation is performed between the keys and the result of the first level. Finally, the result is an encrypted image with two levels of security. The proposed method shows a high safety rate, which achieved an Entropy value rate of 7.997 and a Number of Pixels Changing Rate (NPCR) of 100% on the test image group. [ABSTRACT FROM AUTHOR]

Partitioning or segmenting intensity inhomogeneity colour images is a challenging problem in computer vision and image shape analysis. Given an input image, the active contour model (ACM) which is formulated in variational framework is regularly used to partition objects in the image. A selective type of variational ACM approach is better than a global approach for segmenting specific target objects, which is useful for applications such as tumor segmentation or tissue classification in medical imaging. However, the existing selective ACMs yield unsatisfactory outcomes when performing the segmentation for colour (vector-valued) with intensity variations. Therefore, our new approach incorporates both local image fitting and saliency maps into a new variational selective ACM to tackle the problem. The euler-lagrange (EL) equations were presented to solve the proposed model. Thirty combinations of synthetic and medical images were tested. The visual observation and quantitative results show that the proposed model outshines the other existing models by average, with the accuracy of 2.23% more than the compared model and the Dice and Jaccard coefficients which were around 12.78% and 19.53% higher, respectively, than the compared model. [ABSTRACT FROM AUTHOR]

Protecting information sent through insecure internet channels is a significant challenge facing researchers. In this paper, we present a novel method for image data encryption that combines chaotic maps with linear feedback shift registers in two stages. In the first stage, the image is divided into two parts. Then, the locations of the pixels of each part are redistributed through the random numbers key, which is generated using linear feedback shift registers. The second stage includes segmenting the image into the three primary colors red, green, and blue (RGB); then, the data for each color is encrypted through one of three keys that are generated using three-dimensional chaotic maps. Many statistical tests (entropy, peak signal-noise ratio (PSNR), mean square error (MSE) and correlation) were conducted on a group of images to determine the strength and efficiency of the proposed method, and the result proves that the proposed method provided a good level of safety. The obtained results were compared with those of other methods, and the result of comparing confirms the superiority of the proposed method. [ABSTRACT FROM AUTHOR]

There are many data hiding algorithms in which the quality of images is degraded during data concealing and extracting. Thus, now a day such methods are required that can recover the image as well as data during extraction called reversible data hiding methods. The existing reversible data hiding methods provide good quality with the low capacity or poor quality with the high capacity because of the quality and capacity are entirely related to each other. Thus there is a dire need to develop a method which can provide good quality as well as capacity. In this paper, a reversible data hiding (RDH) technique for colour image based on prediction error expansion (PEE) with efficient pixel selection is presented. In traditional methods, the local variance of the grayscale image is used as the pixel selection parameter as it is proportional to the prediction error (PE). Considering that different colour channels contribute by different amount in the formation of grey image, we propose a pixel selection technique where the local variance of the colour channels is also used along with that of grayscale image to improve the quality of the selected pixels as embedding in pixels with lower magnitude PEs will yield lower distortion. Also to improve the embedding capacity of the RDH technique, double embedding in one of the colour channel has been proposed which will again be achieved by pixel selection among the selected pixels. [ABSTRACT FROM AUTHOR]

In comparison with integer-order chaotic systems, fractional-order chaotic systems exhibit more complex dynamics. In recent years, research into fractional chaotic systems for the utilization of image cryptosystems has become increasingly highlighted. This paper describes the development, testing, numerical analysis, and electronic realization of a fractional-order memcapacitor. Then, a new four-dimensional (4D) fractional-order memcapacitive hyperchaotic system is suggested based on this memcapacitor. Analytically and numerically, the nonlinear dynamic properties of the hyperchaotic system have been explored, where various methods, including equilibrium points, phase portraits of chaotic attractors, bifurcation diagrams, and the Lyapunov exponent, are considered to demonstrate the chaos behaviour of this new hyperchaotic system. Consequently, an encryption cryptosystem algorithm is used for colour image encryption based on the chaotic behaviour of the memcapacitive model, where every pixel value of the original image is incorporated in the secret key to strengthen the encryption algorithm pirate anti-attack robustness. For generating the keyspace of that employed cryptosystem, the initial condition values, parameters, and fractional-order derivative value(s) (q) of the memcapacitive chaotic system are utilized. The common cryptanalysis metrics are verified in detail by histogram, keyspace, key sensitivity, correlation coefficient values, entropy, time efficiency, and comparisons with other recent related fieldwork in order to demonstrate the security level of the proposed cryptosystem approach. Finally, images of various sizes were encrypted and recovered to ensure that the utilized cryptosystem approach is capable of encrypting/decrypting images of various sizes. The obtained experimental results and security metrics analyses illustrate the excellent accuracy, high security, and perfect time efficiency of the utilized cryptosystem, which is highly resistant to various forms of pirate attacks. [ABSTRACT FROM AUTHOR]

Depth maps are used to describe object positioning information in three‐dimensional (3D) space, and they are crucial for RGB‐D data representation, which is useful for numerous interactive visual applications. In practice, depth maps are often contaminated by compound noise, including intrinsic noise and missing regions owing to active illumination shadows. As existing noise models cannot describe the above‐mentioned compound noise effectively, the subsequent filter design is a challenging task. In this study, an adaptive colour‐guided non‐local mean (NLM) filter is proposed to address such compound noise. First, the authors classify the depth map into hole and non‐hole pixels. Then, the proposed filter is designed on the basis of the NLM framework, where the colour image is used as a guide prior for hole‐artifact removal. Finally, the authors use a shock filter to effectively address the non‐regularisation of the restored depth map edges and remove the remaining noise. Experiments show that the proposed filter qualitatively and quantitatively outperforms existing colour‐guided and unguided filters. Moreover, the authors verify the superiority of the proposed filter through virtual view synthesis and 3D scene reconstruction applications. [ABSTRACT FROM AUTHOR]

Copyright of Experimental Technology & Management is the property of Experimental Technology & Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Chest x-ray medical images are widely used for diagnostic purposes for several reasons including it available, attainable and excellent imaging of hard tissues like bones, but there is difficulty in imaging of the soft tissues, moreover the saturated colour of the x-ray image causing intricacy to read it, therefore, turned attention to the colorization process which can be used to transform the grayscale medical images to the colour medical images. In this paper, a new pseudo-coloring method proposed for colorizing the frontal chest x-ray medical images which are very important for disease detection and recognition. The key idea of this method is applying different and various experimental mathematical equations on the proposed medical sample image, which it belongs to the patient with Hydatid cyst parasite disease in the lung. The counterfeit coloring had intense contribute in enhancing of the visual attractiveness of medical images, the output colored images have a better visual description, it has a possibility to describe hidden information better than a conventional monochromatic image, this is an excellent indicator of the algorithm's suitability for the purpose for which it was formulated.

Gasoline and two types of biomass, i.e. shrub boughs and pine boughs were investigated experimentally. The gasoline was the mixture of 500 mL water and 300 mL 92‐octane gasoline. The experimental measurement was conducted on a device that contained a colour camera (SP‐20000C) and a fibre optic spectrometer (AvaSpec‐2048). The device captured spectral intensities via the spectrometer. Colour images were captured on the colour camera. The radiation characteristics, i.e. the wavelength‐dependent emissivity in this study, were determined with a multi‐wavelength thermometry in accordance with the spectral intensities. The results of emissivity were used so that the temperature distribution was calculated directly using the colour image, with the consideration of the broad response spectrum of the channels of the camera. Radiation characteristics and temperature distributions for these three types of flame were experimentally determined and presented. Results show that, in the visible light region, excluding the spectral lines of alkali metals, the continuous radiation of these flames should result from the similar substance. What is more, the combustion of gasoline (watered) is the most incomplete, resulting in a mass of product of incomplete reaction, and pine boughs were more flammable than shrub boughs. [ABSTRACT FROM AUTHOR]

At present, the binary images are often used as the original watermark images of many watermarking methods, but partial methods cannot be easily extended to colour image watermarking methods. For resolving this problem, we propose a new watermarking method using ternary coding and QR decomposition for colour image. In the procedure of embedding watermark, the colour image watermark is coded to ternary information; the colour host image is also separated into image blocks of sized 3 × 3, and these image blocks are further decomposed via QR decomposition; then, one ternary watermark is embedded into one orthogonal matrix Q of QR decomposition by the proposed rules. In the procedure of extracting watermark, the proposed method uses the blind-manner to extract the embedded ternary information. The novelty of this scheme lies in the proposed ternary coding for watermark image, which can improve the imperceptibility, embedded watermark capacity and real-time feature of the watermarking scheme. The results of simulation show the presented technique is better than other compared schemes with respect to imperceptibility, embedded watermark capacity and real-time feature under the similar robustness. [ABSTRACT FROM AUTHOR]

This paper presents a new scheme for encryption of single-channel colour images. The scheme uses amplitude- and phase-truncation approach to introduce non-linearity for enhanced security. Further, the colour image encryption is performed in the fractional Hartley domain, which is relatively less investigated. The encryption starts with an affine transform of each channel of the input colour image. Thereafter, one of the channels is considered as the input amplitude image while the other two are used as phase masks, one in the spatial and the other in the frequency domain. A detailed analysis of the scheme's sensitivity to various encryption parameters has been carried out. In addition, security analysis of the scheme against attacks establishes the scheme's robustness. The combined use of the affine transform and phase-truncation approach for colour image encryption in the fractional Hartley domain is attempted for the first time in this study. It is shown that the proposed scheme resists the special attack. [ABSTRACT FROM AUTHOR]

An encryption scheme for colour images using a spatiotemporal chaotic system is proposed. Initially, we use the R, G and B components of a colour plain-image to form a matrix. Then the matrix is permutated by using zigzag path scrambling. The resultant matrix is then passed through a substitution process. Finally, the ciphered colour image is obtained from the confused matrix. Theoretical analysis and experimental results indicate that the proposed scheme is both secure and practical, which make it suitable for encrypting colour images of any size.

Copyright of Journal of Kufa - Physics is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Here, the authors present an effective regularisation approach to colour image demosaicking. The authors' work is inspired by the interesting observation that the cross‐channel dependencies of high‐frequency details of a colour image are supposed to correspond in all the main colour channels acquired by the sensor. Therefore, minimising their difference in the demosaicking process can significantly improve the quality of the reconstructed image. The authors also demonstrate that mosaicked image formation strictly depends on the intrinsic lens blur. Hence, in the authors' solution to the image demosaicking as an inverse imaging problem, they take the lens blur characteristics into account. The proposed regularisation method is also based on the fact that sensor saturation significantly alters the distribution of pixel intensity and Gaussian noise. The authors develop an efficient solution to the problem via the alternating direction method of multipliers numerical solver. As a result of these steps, the proposed demosaicking approach significantly enhances the quality of reconstructed images. Experimental results and quantitative evaluations demonstrate that the proposed method outperforms the existing image demosaicking methods. [ABSTRACT FROM AUTHOR]

In this paper, a novel steganography algorithm based on local reference edge detection technique and exclusive disjunction (XOR) property is proposed. Human eyes are less sensitive towards intensity changes in the sharp edge region compared to the uniform region of the image. Because of this, the secret message bits have been embedded in the sharp regions by local reference pixels which are detected by Canny edge method and optimized by dilation morphological operator. The predefined sets of pixels are easily identified with less computational complexity in the stego image. The embedding algorithm improved in terms of security and capacity using bit plane dependent XOR coding technique that makes least possible alterations in LSB bits of edge pixels. The existing edge-based steganography techniques provide better imperceptibility but relatively limits the embedding capacity. The proposed method efficiently improves the embedding capacity with an acceptable range of imperceptibility and robustness. The simulation results evaluated using full reference image quality assessment method, it exhibits better embedding capacity (bpp) compared to existing steganography techniques retaining the values of PSNR and structural similarity (SSIM). [ABSTRACT FROM AUTHOR]

Due to the complexity of underlying data in a color image, retrieval of specific object features and relevant information becomes a complex task. Colour images have different color components and a variety of colour intensity which makes segmentation very challenging. In this paper we suggest a fitness function based on pixel-by-pixel values and optimize these values through evolutionary algorithms like differential evolution (DE), particle swarm optimization (PSO) and genetic algorithms (GA). The corresponding variants are termed GA-SA, PSO-SA and DE-SA; where SA stands for Segmentation Algorithm. Experimental results show that DE performed better in comparison of PSO and GA on the basis of computational time and quality of segmented image. [ABSTRACT FROM AUTHOR]

Mexican apple production suffers high losses due to poor handling in processing. Implementation of a straightforward, low cost method to sort apples by their ripening stage is required. A set of Golden Delicious apples was used to monitor their physicochemical properties and external colour, a second set of apples was used to validate the method. To classify the stages, a ripening index (RPI) was proposed, in which three stages were identified; unripe, ripe and senescent. Weibull model was applied to the physicochemical parameters in order to describe their kinetic behaviour. The three RPI stages were compared with colour variability using the CIELab colour space, chroma ( C ∗ ) and hue angle ( h ∗ ), allowing the identification of the three ripening stages. Principal component analysis was used to evaluate the correlation between variables. A first correlation was performed between physicochemical and colour parameters and variables correlated correctly between each other except for L ∗ , but both described the samples variability with 91.05% reliability. Using only colour parameters, the samples were described accurately with 95.06% reliability. Multivariate discriminant analysis (MDA) was done in order to validate the method. A cross-validation was performed with an initial set of apples used as trial samples and a second set of apples for validation. MDA was capable of classifying apples in their correct ripening stage with 100% accuracy. A second analysis was carried out using four colour parameters ( a ∗ , b ∗ , C and h ∗ ), and results indicated that the ripening stages can be classified with 100% accuracy. [ABSTRACT FROM AUTHOR]

Optimising computing times of applications is an increasingly important task in many different areas such as scientific and industrial applications. Graphics processing unit (GPU) is considered as one of the powerful engines for computationally demanding applications since it proposes a highly parallel architecture. In this context, the authors introduce an algorithm to optimise the computing time of feature extraction methods for the colour image. They choose generalised Fourier descriptor (GFD) and generalised colour Fourier descriptor (GCFD) models, as a method to extract the image feature for various applications such as colour object recognition in real‐time or image retrieval. They compare the computing time experimental results on central processing unit and GPU. They also present a case study of these experimental results descriptors using two platforms: a NVIDIA GeForce GT525M and a NVIDIA GeForce GTX480. Their experimental results demonstrate that the execution time can considerably be reduced until 34× for GFD and 56× for GCFD. [ABSTRACT FROM AUTHOR]

Object detection is an essential function of robotics based agricultural systems and many algorithms exist for this purpose. Colour although an important characteristic is often avoided in place of faster grey-scale implementations or is only used in an rudimentary arrangement. This study presents the Colour Feature Extreme Learning Machine (CF-ELM), which is an implementation of the extreme learning machine (ELM), with a partially connected hidden layer and a fully connected output layer, taking three colour inputs instead of the standard grey-scale input. The CF-ELM was tested with three different colour systems including HSV, RGB and Y’UV and compared for time and accuracy against the standard grey-scale ELM. The four implementations were tested on three different datasets including weed detection, vehicle detection and stock detection. It was found that the colour implementation performed better overall for all three datasets and the Y’UV was best performing colour system on all tested datasets. With the Y’UV delivering the highest accuracy in weed detection at 84%, 96% in vehicle detection and 86% in stock detection. Along side the CF-ELM, an algorithm is introduced for desktop based classification of objects within a pastoral landscape, with individual speeds between 0.06 s and 0.18 s for a single image, tested within each colour space. The algorithm is designed for use in a scenario that provides difficult and unpredictable terrain, making it ideal for use in an agricultural or pastoral landscape. [ABSTRACT FROM AUTHOR]