Digital Color Images Research Articles

Classification of bitter and sweet olives using image processing and artificial neural networks during curing process in brine and water environments

ABSTRACTThe external appearance of an olive’s skin is the most decisive factor in determining its quality. In order to quantify the colour changes that occur during sweetening process, a computer vision systems based on Artificial Neural Networks (ANN) was developed to determine bitter and sweet olives. To this end, olives were treated in brine and water testing environments for nine days. During this process, digital colour image were taken every two days. Two colour spaces (RGB and L*a*b*) were used and six colour features corresponding to average of each colour channel were derived and used for ANN training. The overall accuracy of ANN classifier was of 93.38%. According to the results of the image analysis, the L*, R, G and B values showed a significant correlation with general acceptance for water curing treatment (p < 0.05). For brine curing treatment, results showed a significant correlation between L*, a*, b*, R and G with general acceptance (p < 0.05). Considering the results of sensory analysis the optimum time for both brine and distilled water were seven and three, respectively. Furthermore, brine curing had a greater impact on olive skin-colour changes.

DNA Chaos Blend to Secure Medical Privacy

In this technological era, it is highly essential to protect the digital medical data from the fraud and forgery as they are transmitted over the public channel. Also with the increased data traffic, it is hard to transmit the entire bulky medical data. New methods have come into the scene to reduce the traffic while maintaining the sufficient level of security. Partial encryption is one of the methods which selectively encrypt the bulky medical image. Meanwhile, if the same medical image is needed to be reused for another diagnosis, then it is recommended to protect the entire medical image. This paper proposes a hybrid encryption scheme based on deoxyribo nucleic acid and chaotic maps, which can be adaptable for both selective and full medical image encryption. The proposed algorithm uses multiple chaotic maps in single process to generate the highly random keys for encrypting the color digital imaging and communications in medicine image. The algorithm comprises three phases, namely, permutation, encoding, and diffusion. In all the phases, the selection of specific rule set depends on the key sequences produced from the combined chaotic system. Experimental results are carried out to validate the resistance of the developed algorithm toward statistical, differential, and brute force attacks.

ESTIMATING CROP COVER FRACTION FROM DIGITAL COLOR IMAGES

Abstract. The use of automated methods to estimate crop cover fraction from digital color images has increased in recent years. Crop cover fraction can determine accurate, fast and inexpensive with this methods. A digital color images was acquired over each of the 30 sample fields in 2014 year at 2–3 week intervals. Study area has 15 sunflower fields and 15 corn fields. Digital color images were collected during 4 months, namely over the course of the growing season from sowing until harvesting to determine crop cover fraction. We used two approach to estimate crop cover fraction. In first method, the images were transformed from the RGB (red, green, blue) color space to the HSI (hue, intensity, saturation) color space. We used an object-based image analysis approach to classify the images into green vegetation and the other materials. In the second method, The Green Crop Tracker is less labor and time intensive than the object-based classification approach, is a viable alternative to ground-based methods. By comparing object-based classification method and Green Crop Tracker software 2014 growing season, results were obtained: There were high correlations between the estimations obtained by object-based classification method and Green Crop Tracker software (for 2014 R2 = 0.89). The relationship between two methods for 2014-23 sunflower field was calculated R2 = 0.97.

A review of chemical 'spot' tests: A presumptive illicit drug identification technique.

Chemical 'spot' tests are a presumptive illicit drug identification technique commonly used by law enforcement, border security personnel, and forensic laboratories. The simplicity, low cost, and rapid results afforded by these tests make them particularly attractive for presumptive identification globally. In this paper, we review the development of these long-established methods and discuss color test recommendations and guidelines. A search of the scientific literature revealed the chemical reactions occurring in many color tests are either not actively investigated or reported as unknown. Today, color tests face many challenges, from the appearance of new psychoactive substances to concerns regarding selectivity, sensitivity, and safety. Advances in technology have seen color test reagents used in digital image color analysis, solid sensors, and microfluidic devices for illicit drug detection. This summarizes current research and suggests the future of presumptive color testing.

Multi-layer security of color image based on chaotic system combined with RP2DFRFT and Arnold Transform

The security system for RGB image information is very critical issue in current time. In this security system, we have proposed an algorithm for encryption and decryption of RGB images by using chaotic system based scrambling combined with reality preserving two dimensional discrete fractional Fourier transform (RP2DFRFT) and Arnold transform (AT). Earlier developed security system for RGB image data provides only one layer of protection either in time domain or in frequency domain. But presented cryptosystem provides multi-layer security for RGB image in time as well as in frequency domain with no loss of any information of red (R), green (G) and blue (B) components. The algorithms of existing techniques for the security of color images are mostly based on keys, but the proposed cryptosystem provides security of color images on the basis of the keys as well as the arrangement of used algorithms and parameters. Additionally, the use of reality preserving method not just eliminates the complexity of dealing with imaginary data, but it also enhances the efficiency of the technique by reducing the domain space to its half, at least for all the calculations involved in two dimensional DFRFT. The sensitivity analysis of the proposed technique represents that the encryption keys are very sensitive. Results on standard examples and their security and statistical analysis for color images are testimony to the robustness and appropriateness of the presented technique. This method would find a large applications in digital color image processing and security of color image transmission in open network.

A Fiber Bundle Geometry Approach for Edge Detection of Chromaticity Distributions

Differential structures are useful for image processing and chromaticity involves additional information with respect to just intensity. In this letter, we interpret digital color image chromaticity as a fiber bundle manifold, and introduce a differential geometry object so(3) Lie-algebra valued gauge field. The gauge field is structure preserving in the sense which is invariant with respect to a certain symmetry transformations of image chromaticity, so can be used to define invariant edge detections, e.g., edge strength of chromaticity distribution of color images. Two numerical examples are shown for illustration.

Color display and encryption with a plasmonic polarizing metamirror

Abstract Structural colors emerge when a particular wavelength range is filtered out from a broadband light source. It is regarded as a valuable platform for color display and digital imaging due to the benefits of environmental friendliness, higher visibility, and durability. However, current devices capable of generating colors are all based on direct transmission or reflection. Material loss, thick configuration, and the lack of tunability hinder their transition to practical applications. In this paper, a novel mechanism that generates high-purity colors by photon spin restoration on ultrashallow plasmonic grating is proposed. We fabricated the sample by interference lithography and experimentally observed full color display, tunable color logo imaging, and chromatic sensing. The unique combination of high efficiency, high-purity colors, tunable chromatic display, ultrathin structure, and friendliness for fabrication makes this design an easy way to bridge the gap between theoretical investigations and daily-life applications.

The geology of the Kerwan quadrangle of dwarf planet Ceres: Investigating Ceres’ oldest, largest impact basin

We conducted a geologic mapping investigation of Dawn spacecraft data to determine the geologic history of the Kerwan impact basin region of dwarf planet Ceres, which is mostly located in the Ac-7 Kerwan Quadrangle. Geological mapping was applied to Dawn Framing Camera images from the Low Altitude Mapping Orbit (LAMO, 35 m/pixel) and supplemented by digital terrain models and color images from the High Altitude Mapping Orbit (HAMO, 135 m/pixel), as well as preliminary Visible and Infrared Spectrometer (VIR) and gravity data. The 284-km diameter Kerwan impact basin is the oldest unequivocal impact crater on Ceres, and has a highly discontinuous, polygonal, degraded rim and contains a ‘smooth’ unit that both fills the basin floor and surrounds the degraded rim to the west, south, and east. Although there are some subtle topographic features in the Kerwan basin that could be interpreted as flow boundaries, there is no indisputable evidence of cryovolcanic features in or around the basin (however if such features existed they could be buried). Nevertheless, all data point to impact-induced melting of a cerean crust enriched in a volatile, likely water ice, to produce the Kerwan smooth material. Subsequent geologic activity in this region includes emplacement of impact craters such as Dantu, which produced a variety of colorful deposits, and rayed craters such as Rao and Cacaguat. Based on the crater size-frequency distribution absolute model ages of the Kerwan smooth material in and around the basin, marking a minimum age for the Kerwan basin, our mapping defines this as the oldest boundary within the cerean geologic timescale, separating the Pre-Kerwanan and Kerwanan Periods at > 1.3 Ga (Lunar-derived chronology model) or > 230–850 Ma (Asteroid-derived chronology model, depending on strength of target material).

Tooth Color Detection Using PCA and KNN Classifier Algorithm Based on Color Moment

Matching the suitable color for tooth reconstruction is an important step that can make difficulties for the dentists due to the subjective factors of color selection. Accurate color matching system is mainly result based on images analyzing and processing techniques of recognition system.  This system consist of three parts, which are data collection from digital teeth color images, data preparation for taking color analysis technique and extracting the features, and data classification involve feature selection for reducing the features number of this system. The teeth images which is used in this research are 16 types of teeth that are taken from RSGM UNAIR SURABAYA. Feature extraction is taken by the characteristics of the RGB, HSV and LAB based on the color moment calculation such as mean, standard deviation, skewness, and kurtosis parameter. Due to many formed features from each color space, it is required addition method for reducing the number of features by choosing the essential information like Principal Component Analysis (PCA) method. Combining the PCA feature selection technique to the clasification process using K Nearest Neighbour (KNN) classifier algorithm can be improved the accuracy performance of this system. On the experiment result, it showed that only using KNN classifier achieve accuracy percentage up to 97.5 % in learning process and 92.5 % in testing process while combining PCA with KNN classifier can reduce the 36 features to the 26 features which can improve the accuracy percentage up to 98.54 % in learning process and  93.12% in testing process. Adding PCA as the feature selection method can be improved the accuracy performance of this color matching system with little number of features.Â

Non-blind digital watermarking with enhanced image embedding capacity using DMeyer wavelet decomposition, SVD, and DFT

Amongst the requirements of digital color image watermarking–capacity is the major component to be addressed effectively. To address the same we proposed a method for inserting a color image into another color image of same size using non-blind watermarking scheme. From this method we achieved reasonably good perceptual similarity by measuring acceptable peak signal to noise ratio (PSNR) and structural similarity (SSIM) index. The method uses DMeyer single level discrete wavelet transformation (DWT) to get approximation coefficients-where most of the image information is stored, discrete Fourier transformation (DFT) is used to get set of components which are sufficient to describe the whole image and singular value decomposition (SVD) to get reliable orthogonal matrix of computationally sustainable components of the transformed image. The method is robust against attacks like–rotation, cropping, JPEG compression and for noises–salt and pepper, gaussian, speckle.

Effective Color image watermarking scheme using YCbCr color space and QR code

A digital image watermarking technique is proposed to hide the relevant information in color digital images. The image is converted from RGB color space to YCbCr color space. This enables the algorithm to exploit characteristics of the Human Visual System (HVS) for embedding the watermark. The scheme embeds the watermark information utilizing wavelets transforms and Singular Value Decomposition (SVD) for this purpose. It uses a Quick Response (QR) code as the watermark. The QR code is a robust code from which embedded information can be extracted even if the retrieved QR code image is distorted. Thus the proposed technique employs a judicious combination of different algorithmic ideas including altered YCbCr color space, transformation into wavelet domain, SVD for selection of places to embed and QR codes for enhanced robustness. The watermarking scheme proposed is robust against various signal processing attacks (e.g. filtering, compression, noise addition etc.) as well as geometric attacks (e.g. rotation, cropping etc.). Computational experiments on a variety of cover images show that embedding QR code is more effective than the other watermarks in terms of better information carrying capacity, robustness and imperceptibility. The proposed scheme is novel and effective as it simultaneously provides advantages of each of the individual elements combined in this approach.

Adaptive removable visible watermarking technique using dual watermarking for digital color images

This paper proposes a removable visible watermarking system based on a dual watermark technique and blind removal. A visible watermark pattern is embedded in the cosine discrete transform (DCT) domain, taking into consideration the texture and luminance features of the watermark and host images to create a visible watermarked image. To prevent illegal visible watermark removal, the original watermark is embedded in an invisible manner in the visible watermarked image by employing the Quantization Index Modulation-Dither Modulation (QIM-DM) technique, thus ensuring that the original watermark cannot be obtained by malicious attacks. The visible watermark removal process is carried out using only the correct user’s keys, without the need for additional information, such as the original watermark or the original host image, which allows a high-quality image to be obtained; however, if the user’s keys used in the removal process are wrong, the visible watermarked image suffers higher distortion in its content, even in non-visible watermarked regions. The experimental results show that the proposed system outperforms previous related works in terms of blind removal, preservation of the quality of the unmarked recovered image, and higher visual degradation of the content in the recovered image if an illegal removal attempt is performed.

Skema Digital Watermarking Citra dengan Metode TLDCT dan Chinese Remainder Theorem

Currently, it is easy to access the wide variety of digital content on the internet, and therefore protection effort for digital content is an important problem that needs to solve. One kind of digital content that urgently needs to protect is digital image. Protection is needed not only for the copyright but also for the authenticity of digital image because there are so many advanced image editing software, that are easy to use. This paper presents a scheme for digital image protection through Digital Watermarking process using Two Level Discrete Cosine Transform, and Chinese Remainder Theorem for color digital image. This scheme has an ability to detect and to recover some kind of changes that occur in the watermarked image. This ability can be achieved because this scheme is categorized into fragile digital watermarking, thus, has low robustness. However, based on experiment results, this scheme shows a good invisibility. It is higher than the previous research and has a minimum distortion, proven by Peak Signal to Noise Ratio (PSNR) value of around 45.

Highly selective vapochromic fluorescence of polycarbonate films Doped with an ICT‐Based solvatochromic probe

ABSTRACTThe vapochromic properties of a fluorescent 3‐[2‐(4‐nitrophenyl) ethenyl]‐1‐(2‐ethylhexyl)‐2‐methylindole (NPEMI‐E) characterized by intramolecular charge transfer (ICT) character, dispersed in polycarbonate (PC) films is reported. NPEMI‐E solvatochromism is investigated by means of experimental and computational methods. Fluorescent PC films containing 0.1 wt % of NPEMI‐E are prepared and exposed to saturated atmospheres of different volatile organic compounds (VOCs). NPEMI‐E/PC films show remarkable and reversible vapochromism when exposed to VOCs with high polarity index and favorable interaction with PC matrix such as CHCl3. Only minor variations in the emission wavelength are actually recorded for all other classes of VOCs investigated. The hue parameter is also used for the effective extraction of spectral information from digital color images without the need for wavelength discriminators. Overall, the present results support the use of NPEMI‐E/PC films for the cost‐effective detection of CHCl3 vapors. © 2017 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2017, 55, 1171–1180

Gradient-guided color image contrast and saturation enhancement

Digital color images are capable of presenting hue, saturation, and brightness perceptions. Therefore, quality improvement of color images should be taken into account to enhance all three stimuli. An effective method is proposed that aims at enriching the colorfulness, vividness, and contrast of color images simultaneously. In this method, color correction based on magnitude stretching is carried out first, image enhancement is then derived from an intensity-guided operation that concurrently improves the contrast and saturation qualities. Furthermore, the proposed methodology mitigates the heavy computational burden arising from the need to transform the source color space into an alternative color space in conventional approaches. Experiments had been conducted using a collection of real-world images captured under various environmental conditions. Image quality improvements were observed both from subjective viewing and quantitative evaluation metrics in colorfulness, saturation, and contrast.

Color removal method considering perceived lightness

A novel color removal method for digital color images is proposed. In this method, differences of colors in an input color image are reflected effectively, and the perceived lightness coming from the input color image is preserved as much as possible in order to realize the natural color-to-gray conversion. The effectiveness and the validity of the proposed method are verified by some experiments.

Multispectral and joint colour-texture feature extraction for ore-gangue separation

Ore sorting is a useful tool to remove gangue material from the ore and increase the quality of the ore. The vast developments in the area of artificial intelligence allow fast processing of full color digital images for the preferred investigations. Three different approaches to color texture analysis were used for the classification of associated gangue from limestone and iron ore. All the methods were based on extensions of the co-occurrence matrix method. The first approach was a correlation method, in which co-occurrence matrices are computed both between and within the color bands. In the second approach, joint color-texture features, where color features were extracted from chrominance information and texture features were extracted from luminance information of the color bands. The last approach used grey scale texture features computed on a quantized color image. Results showed that the joint color-texture method was 98% accurate for limestone and 98.4% for iron ore gangue classification. It was further observed that the features showed better accuracy with 64 grey levels quantization.

Spatially resolved thickness determination of rough thin films by reflectometry with polychromatic light.

This article introduces a simple metrology set-up based on white light interference. The aim is to determine the thickness of thin transparent films by their reflection color under white illumination. Therefore, one digital color image of a large field of view is taken in nontelecentric geometry. To obtain reflected light at all angles of view without having to move the camera the substrate has to be sufficiently rough. Additionally, interference occurs at the thin transparent film covering the substrate surface from which a two-dimensional lateral thickness distribution can be calculated. This method has been used as industrial inline process control for a CdS semiconductor layer on top of a rough Cu(In,Ga)(Se,S)2 thin film solar absorber and yielded 74 nm film thickness with only a 1 nm standard deviation. Options to further reduce the standard deviation with different illuminants and other cameras are proposed.

ANALYSIS OF OVARIAN DISEASES USING ULTRASOUND IMAGES

Ovarian disease is the most common disease occurring in female reproductive organs. The premature recognition and action needed for diagnosis the disease to avoid infertility or cancer to them. The reason behind infertility is Polycystic Ovary Syndrome (PCOS) and the Ovarian Regenerative Tissues Cells. PCOS is the kind of endocrine disorder present in female’s ovary and creates problem with Irregular menstrual periods, skin diseases, excess hair growth in body and face, acne and finally infertility. For ovarian regenerative tissues cells histopathology slides can be well stored put away in digitized color image design. One of the well known determination inclinations to recognize ovarian tissues is ultrasound image scanner. In any case, because of various shape, size and color, distinguishing proof of ovarian tissues is a testing assignment for ultrasound scanners as it procedure dark scale images. In order to overcome these diseases, we proposed techniques for ultrasound images. By this techniques follicle in the ovary and the ovarian regenerative tissues cells is automatically detected.

A novel quantum representation of color digital images

In this paper, we propose a novel quantum representation of color digital images (NCQI) in quantum computer. The freshly proposed quantum image representation uses the basis state of a qubit sequence to store the RGB value of each pixel. All pixels are stored into a normalized superposition state and can be operated simultaneously. Comparison results with the latest multi-channel representation for quantum image reveal that NCQI can achieve a quadratic speedup in quantum image preparation. Meanwhile, some NCQI-based image processing operations are discussed. Analyses and comparisons demonstrate that many color operations can be executed conveniently based on NCQI. Therefore, the proposed NCQI model is more flexible and better suited to carry out color quantum image processing.