Digital Color Images Research Articles

DCT-based color digital image blind watermarking method with variable steps

In this paper, a blind watermarking method for color digital image based on DCT domain with variable steps is proposed to solve the copyright protection of color digital image. In this method, partial DCT coefficients of the image block transformed by two-dimensional discrete cosine transform (2D-DCT) are selected in the transform domain firstly, then these selected DCT coefficients at different positions are quantized by different quantization steps, and the embedding and blind extraction of digital watermark are completed. This method used color digital image as watermark image instead of gray image or binary image, and the color host image used in this scheme is selected from two public image databases (CVG-UGR and USC-SIPI). The experimental result shows that this scheme embedded color digital image watermark into host image successfully not merely has high invisibility, but also has strong robustness, which is suitable for digital image copyright protection.

Color image quantization with peak-picking and color space

Color image quantization is a significant procedure of reducing the huge range of color values of a digital color image into a limited range. In this paper, an automated clustering of pixels and color quantization algorithm is proposed. The ideal number of representative colors is unknown beforehand in most color quantization algorithms. This is an important handicap in most practical cases. The proposed color quantization approach (PPCS) is able to automatically estimate an appropriate number of colors in a quantized palette. Hence, PPCS requires no number of representative colors to be set in advance. This algorithm has two main steps to follow: color palette design and pixel mapping. The color palette is generated by the combination of the entire peaks of all color component histograms. Such that, all color component histogram was smoothed in order to remove unreliable peaks. Next, unreliable colors will be removed from the palette. Then, each pixel in the image will be assigned to the cluster (unit color in the palette) which has the least Euclidean distance. To evaluate the ability of the PPCS, 22 images from Berkeley segmentation dataset have been randomly selected and tested with PPCS and also by two well-known quantization algorithms. The numerical evaluations have been carried out by using computation time, PSNR, MSE, and SSIM performance criteria. Both visual and numerical evaluations reveal that the proposed method presents promising quantization results. Such that, PPCS is ranked first, second, first and first according to PSNR, MSE, SSIM and computation time, respectively.

Face Detection Based On Eye-Mouth Triangular Approach

Human face is a complex and dynamic structure. It is a challenge to be able to make a face recognition system like humans. At the beginning of its development, many facial recognition studies only focused on facial features. In 1991, Turk and Pentland developed a face recognition system based on Principal Component Analysis named eigenface. This system is very efficient because it only focuses on components that most affect facial image. However, this system has weaknesses, which cannot be used to determine the position of the face. In this final project, image processing methods will be carried out to detect faces in digital images. The method used is eye mouth triangular approach with the steps being taken are skin detection, eye detection, mouth detection, and facial confirmation. From the results of a hundred digital color images tested, there were 82 images that were successfully detected. The main system failure is caused by failure in skin detection. Further development is needed so that the system can work optimally.

Stable Backward Diffusion Models that Minimise Convex Energies

The inverse problem of backward diffusion is known to be ill-posed and highly unstable. Backward diffusion processes appear naturally in image enhancement and deblurring applications. It is therefore greatly desirable to establish a backward diffusion model which implements a smart stabilisation approach that can be used in combination with an easy-to-handle numerical scheme. So far, existing stabilisation strategies in the literature require sophisticated numerics to solve the underlying initial value problem. We derive a class of space-discrete one-dimensional backward diffusion as gradient descent of energies where we gain stability by imposing range constraints. Interestingly, these energies are even convex. Furthermore, we establish a comprehensive theory for the time-continuous evolution and we show that stability carries over to a simple explicit time discretisation of our model. Finally, we confirm the stability and usefulness of our technique in experiments in which we enhance the contrast of digital greyscale and colour images.

Enhancement of Security and QoS in Wireless Medical Sensor Networks

Wireless medical sensor networks (WMSN) collect the data of a patient’s vital body parameters using wearable or nonwearable biosensors. Since WMSN is wireless in nature there occur numerous issues like a false alarm, lack of robustness, and low processor speed, which reduce the system’s effectiveness. One of the major issues is the security and privacy protection of the collected data and providing a greater Quality of Service (QoS) for the network in terms of energy efficiency, standardization, etc. Targeting these problems, we introduced a hybrid secure and fuzzy fusion system to achieve efficient secure transmission and data fusion in WMSN. The basic idea of the proposed method is to generate a private key from specific features of the digital color image; the generated key is encrypted by the Advanced Encryption Standards (AES) mechanism. The proposed system handles the vague and imprecise data to reduce energy consumption and increases the network lifetime. The inference results verify the efficiency of the proposed method in terms of security and energy consumption of the network.

High Security and Capacity of Image Steganography for Hiding Human Speech Based on Spatial and Cepstral Domains

A new technique of hiding a speech signal clip inside a digital color image is proposed in this paper to improve steganography security and loading capacity. The suggested technique of image steganography is achieved using both spatial and cepstral domains, where the Mel-frequency cepstral coefficients (MFCCs) are adopted, as very efficient features of the speech signal. The presented technique in this paper contributes to improving the image steganography features through two approaches. First is to support the hiding capacity by the usage of the extracted MFCCs features and pitches extracted from the speech signal and embed them inside the cover color image rather than directly hiding the whole samples of the digitized speech signal. Second is to improve the data security by hiding the secret data (MFCCs features) anywhere in the host image rather than directly using the least significant bits substitution of the cover image. At the recovering side, the proposed approach recovers these hidden features and using them to reconstruct the speech waveform again by inverting the steps of MFCCs extraction to recover an approximated vocal tract response and combine it with recovered pitch based excitation signal. The results show a peak signal to noise ratio of 52.4 dB of the stego-image, which reflect a very good quality and a reduction ratio of embedded data to about (6%–25%). In addition, the results show a speech reconstruction degree of about 94.24% correlation with the original speech signal.

Image enhancement with lightness correction and image sharpening based on characteristics of vision for elderly persons

In general, as people age the functions of their sensory organs deteriorate. For example, in the eye of an elderly person, the visual field becomes dark owing to a decrease in the amount of light reaching the retina. Moreover, objects appear blurred due to a decrease in contrast sensitivity. In particular, the contrast sensitivity decreases remarkably as the spatial frequency increases. In this study, we propose an image enhancement method that considers the visual characteristics of elderly persons. The proposed method combines lightness correction and amplification of high spatial frequency components to obtain images with optimized visibility for elderly persons. In particular, lightness enhancement that guarantees color gamut via tone mapping is conducted. In addition, image sharpening is applied based on the inverse characteristic function of the contrast sensitivity curve. The experiments were performed using several digital color images to confirm the effectiveness of the proposed method.

Deep Learning Based Switching Filter for Impulsive Noise Removal in Color Images.

Noise reduction is one of the most important and still active research topics in low-level image processing due to its high impact on object detection and scene understanding for computer vision systems. Recently, we observed a substantially increased interest in the application of deep learning algorithms. Many computer vision systems use them, due to their impressive capability of feature extraction and classification. While these methods have also been successfully applied in image denoising, significantly improving its performance, most of the proposed approaches were designed for Gaussian noise suppression. In this paper, we present a switching filtering technique intended for impulsive noise removal using deep learning. In the proposed method, the distorted pixels are detected using a deep neural network architecture and restored with the fast adaptive mean filter. The performed experiments show that the proposed approach is superior to the state-of-the-art filters designed for impulsive noise removal in color digital images.

Integrated Partial Encryption and Watermarking Technique for Digital Video using Chaos and Support Images

Encryption and Watermarking are image processing tools that are used mostly separately. Encrypting a document completely obscures it and watermarking is applied mostly for copy right protection. For entertainment type videos, partial encryption and watermarking may be integrated such that both objectives are attained. We report in this paper a novel combined partial encryption and watermarking algorithm for digital videos using chaotic system and support image. Watermarks are generated by using iris information of the authentic user or the authentic producer of the digital video. Watermarks of full size and half size are embedded in the luminance frame (s) of the video using simple LSB steganography. A sequence of color frames is watermarked in two phases, and partially encrypted in two layers, the watermarks considered are encrypted before embedding. The luminance frame (s) is (are) preprocessed before embedding with the watermarks to defy stega-analysis. Chaotic logistic map and a gray level support digital image is used for obtaining unique row/column sequences as well as for generating robust random binary sequences. A support color digital image is used in the first layer encryption of the digital video. Modified Rabinovich 4 dimensional hyper-chaotic system is used for second layer encryption. Encryption algorithm is applied in R, G, B frames separately. The technique may also be applied for integrated encryption and watermarking of digital images.

The genus Lepisiota Santschi, 1926 of the Arabian Peninsula with the description of a new species, Lepisiota elbazi sp. nov. from Oman, an updated species identification key, and assessment of zoogeographic affinities

This study updates and summarizes information on the taxonomy and status of the Arabian Lepisiota fauna. We describe and illustrate the new species Lepisiota elbazisp. nov. from the Dhofar Governorate, Oman based on the worker caste. The new species is closest to the Arabian species, L. arabica Collingwood, 1985 from the southwestern mountains of the Kingdom of Saudi Arabia (KSA) and can be separated by having fewer body hairs (two pairs on the posterior margin of the head, two or three pairs on the promesonotum and, one or two pairs on the first gastral tergite), the longer head, scapes, and propodeal spines, and the shorter mesosoma. We present the first illustrated key to the worker caste of the Arabian species of Lepisiota using stacked digital color images to facilitate species determination. The new species is probably endemic to the Dhofar Governorate and seems rare. An up-to-date synoptic checklist of 21 species representing the Arabian Lepisiota Santschi, 1926 is emended based upon the most recent literature in ant systematics. Five species are excluded from the Arabian Lepisiota fauna, L. arenaria (Arnold, 1920), L. erythraea (Forel, 1910), L. incisa (Forel, 1913), L. sericea (Forel, 1892a), and L. simplex (Forel, 1892) for issues related to previous species misidentification. Lepisiota carbonaria (Emery, 1892) is proposed as a senior synonym of L. depilis (Emery, 1897) syn. nov. The faunal composition of Lepisiota species recorded from the Arabian Peninsula can be divided/delineated into two main groups according to their zoogeographical relationships; (1) Afrotropical (11 species-~52.38%); (2) Palearctic (10 species-~47.62%) elements whereas eight species (~38%) are Arabian endemics.

Analysis of a cans waste classification system based on the CMYK color model using different metric distances on the k-means method

This study aims to build and analyze a classification system of can waste based on Cyan, Magenta, Yellow, and Black (CMYK) digital image color model by implementing 3 different metric distances on the k-means method; Manhattan, Euclidean, and Minkowski. The classification results of experimental data note that the implementation of Euclidean distance on the k-means clustering method for classifying the cans waste into three can types has the highest accuracy, with a difference of not more than 1% from Minkowski distance and more than 19.6% from Manhattan distance. The simulation study of various size of generated data show that classification accuracy level using the three metric distances for both the lighting data have a rate less than 70%. The accuracy level of less than 70% in both experimental and simulation data, each of which implements three distances, can be said that this method is not appropriate for building a can classification system.

Combination of minimum wiping pressure and number of wipings that can remove pseudo-skin dirt: A digital image color analysis.

Excessive wiping friction in skin care may lead to skin damage. Bed baths are required to remove skin dirt without affecting the skin barrier function; the wiping pressure and number of wipings that satisfy these two requirements have not been clarified. This study aimed to determine the minimum wiping pressure and number of wipings that can remove skin dirt. In this quasi-experimental study, 50 healthy adults received an adhesion of pseudo-oily and aqueous dirt, randomly assigned to the left and right forearms. Each participant was wiped three times with wiping pressure classified into six randomly assigned categories. The dirt removal rate was calculated by color-analyzing images captured before and after each wiping, and its dependence on the combination of wiping pressure and number of wipings was assessed using a linear mixed model. The combinations achieving oily dirt removal rates of 80% or more were wiping once and pressure ≥50mmHg, wiping twice and pressure ≥40mmHg, and wiping thrice and pressure ≥10mmHg. Aqueous dirt was removed almost completely by wiping once, even with pressure ≥5mmHg. Wiping with at least 10mmHg or more three times can sufficiently remove both oily and aqueous dirt. Dirt removal rates with weak pressure can be made about as effective as those achieved with strong pressure by increasing the number of wipings. This result can be applied to daily nursing, home care, and long-term care health facilities.

Securing Digital Color Image based on Hybrid Substitution Cipher

This study proposes securing digital color images with hybrid substitution cryptographic methods combined with the Vigenere and Beaufort methods. The hybrid process is carried out using the help of two randomly generated keys. The first key is a matrix with an 8-bits value and the second key is a matrix with a binary value. The binary key is used to determine the Vigenere or Beaufort process, while the 8-bit key is used for modulus operations based on the Vigenere or Beaufort algorithm. At the test stage used a standard image that has an RGB color channel as a dataset. The quality of the cryptographic method is measured by several measuring instruments such as MSE, PSNR, and SSIM to determine the quality of encryption visually and the perfection of decryption, besides that it is used Entropy, NPCR and UACI to determine the probability of encryption resistance and quality against differential attacks. The TIC TOC function is also used to measure the computing speed of the encryption and decryption process. Measurement results using all measuring instruments indicate that the proposed method has very satisfying results and has fast computing. Keywords – Cryptography, Substitution Cipher, Modulus Function, Encryption, Decryption, Image Transmission

Quantum Watermarking Scheme based on Spatial Domain and Frequency Domain

Quantum watermarking technology, which is used in anti-counterfeiting and copyright protection, play an important role in the future quantum computer era. To embed more data and reduce image distortion, a novel quantum watermarking method of combining spatial domain and frequency domain is proposed. To this end, the carrier and watermark image are prepared by the novel quantum model of color digital images. The proposed quantum watermarking method is divided into two parts according to the needs of the owner and the importance of the watermarks. These two parts of watermark are embedded into the cover using the spatial and frequency domain. Analysis indicates that the complexity of the watermark separation process increases the difficulty for the attacker to reconstruct the quantum watermarking. Numerical simulation results using MATLAB software shows that this algorithm has better embedding capacity. Not only that, it also has good invisibility and can ensure the security.

Digital Colour Image Steganography for PNG Format and Secured Based on Encoding and Clustering

Digital Colour Image Steganography for PNG Format and Secured Based on Encoding and Clustering

Skewed distribution of leaf color RGB model and application of skewed parameters in leaf color description model

BackgroundImage processing techniques have been widely used in the analysis of leaf characteristics. Earlier techniques for processing digital RGB color images of plant leaves had several drawbacks, such as inadequate de-noising, and adopting normal-probability statistical estimation models which have few parameters and limited applicability.ResultsWe confirmed the skewness distribution characteristics of the red, green, blue and grayscale channels of the images of tobacco leaves. Twenty skewed-distribution parameters were computed including the mean, median, mode, skewness, and kurtosis. We used the mean parameter to establish a stepwise regression model that is similar to earlier models. Other models based on the median and the skewness parameters led to accurate RGB-based description and prediction, as well as better fitting of the SPAD value. More parameters improved the accuracy of RGB model description and prediction, and extended its application range. Indeed, the skewed-distribution parameters can describe changes of the leaf color depth and homogeneity.ConclusionsThe color histogram of the blade images follows a skewed distribution, whose parameters greatly enrich the RGB model and can describe changes in leaf color depth and homogeneity.

A New Genus and Species of Orsillinae (Heteroptera: Lygaeoidea: Lygaeidae) from Argentina

The new genus and species Cuyonysius flavidus, n. gen. and n. sp. (Hemiptera: Heteroptera: Lygaeidae: Orsillinae), described from San Juan Province, Argentina, is tentatively placed in the orsilline tribe Metrargini, based on the lack of a dorsal lobe on the conjunctiva, punctures along the claval suture, and the punctate buccula. Color digital images of the adult male and female, the pygophore, parameres, and aedeagus are provided to help distinguish this new metrargine from closely related taxa. A color habitus image and new distribution records are given for Balionysius maculatus Ashlock.

Using Acoustic Information to Diagnose the Health of A Printer

In addition to colors and shapes, factors of material appearance such as glossiness, translucency, and roughness are important for reproducing the realistic feeling of an image. In general, these perceptual qualities are often degraded when reproduced as a digital color image. The authors have aimed to edit the material appearance of an image as measured by a general camera and reproduce it on a general display device. In their previous study, the authors found that the pupil diameter decreases slightly when observing the surface properties of an object and proposed an algorithm called “PuRet” for enhancing the material appearance based on the physiological models of the pupil and retina. However, to obtain an accurate reproduction, it was necessary to manually adjust two types of adaptation parameters in PuRet as related to the retinal response for each scene and the particular characteristics of the display device. This study realizes the management of the appearance of material objects on display devices by automatically deriving the optimum parameters in PuRet from captured RAW image data. The results indicate that the authors succeeded in estimating an adaptation parameter from the median value of the scene luminance as estimated from a RAW image. They also succeeded in estimating another adaptation parameter from the average value of the scene luminance and the luminance contrast value of the output display device. As a result of an experiment using an unknown display device that was not applied to derive the estimation model, it was confirmed that the proposed model works properly.

Proximal sensing of Urochloa grasses increases selection accuracy

In the American tropics, livestock production is highly restricted by forage availability. In addition, the breeding and development of new forage varieties with outstanding yield and high nutritional quality is often limited by a lack of resources and poor technology. Non-destructive, high-throughput phenotyping offers a rapid and economical means of evaluating large numbers of genotypes. In this study, visual assessments, digital colour images, and spectral reflectance data were collected from 200 Urochloa hybrids in a field setting. Partial least-squares regression (PLSR) was applied to relate visual assessments, digital image analysis and spectral data to shoot dry weight, crude protein and chlorophyll concentrations. Visual evaluations of biomass and greenness were collected in 68 min, digital colour imaging data in 40 min, and hyperspectral canopy data in 80 min. Root-mean-squared errors of prediction for PLSR estimations of shoot dry weight, crude protein and chlorophyll were lowest for digital image analysis followed by hyperspectral analysis and visual assessments. This study showed that digital colour image and spectral analysis techniques have the potential to improve precision and reduce time for tropical forage grass phenotyping.

Reproducible Color Gamut of Hematoxylin and Eosin Stained Images in Standard Color Spaces

A whole-slide imaging (WSI) system is a digital color imaging system used in digital pathology with the potential to substitute the conventional light microscope. A WSI system digitalizes a glass slide by converting the optical image to digital data with a scanner and then converting the digital data back to the optical image with a display. During the digital-to-optical or optical-to-digital conversion, a color space is required to define the mapping between the digital domain and the optical domain so that the numerical data of each color pixel can be interpreted meaningfully. Unfortunately, many current WSI products do not specify the designated color space clearly, which leaves the user using the universally default color space, sRGB. sRGB is a legacy color space that has a limited color gamut, which is known to be unable to reproduce all color shades present in histology slides. In this work, experiments were conducted to quantitatively investigate the limitation of the sRGB color space used in WSI systems. Eight hematoxylin and eosin (H and E)-stained tissue samples, including human bladder, brain, breast, colon, kidney, liver, lung, and uterus, were measured with a multispectral imaging system to obtain the true colors at the pixel level. The measured color truth of each pixel was converted into the standard CIELAB color space to test whether it was within the color gamut of the sRGB color space. Experiment results show that all the eight images have a portion of pixels outside the sRGB color gamut. In the worst-case scenario, the bladder sample, about 35% of the image exceeded the sRGB color gamut. The results suggest that the sRGB color space is inadequate for WSI scanners to encode H and E-stained whole-slide images, and an sRGB display may have insufficient color gamut for displaying H and E-stained histology images.