scholarly journals Mathematics and practice of color space invariants by the example of determining the gray balance for a digital printing system

2020 ◽  
Vol 44 (1) ◽  
pp. 117-126 ◽  
Author(s):  
D.A. Tarasov ◽  
O.B. Milder
Keyword(s):  
Color Space ◽  
Analytical Description ◽  
Digital Printing ◽  
Mutual Transformation ◽  
Color Spaces ◽  
Practical Application ◽  
Printing System ◽  
Cie Lab ◽  
Electrophotographic Printing ◽  
Spatial Curves

In modern printing, a large number of tasks are associated with the mutual transformation of color spaces. In particular, the most common pair of hardware-dependent color spaces is RGB and CMYK, the mutual transformation of colors in which is ambiguous, which creates significant problems in color reproduction. To solve this problem, we propose using color space invariants — gradation trajectories and gradation surfaces, which are analogs of gradation curves for initial colorants and their binary overlays, constructed in the absolute color space of the CIE Lab. Invariants are introduced on the basis of the mathematical apparatus of the differential geometry of spatial curves and surfaces. Practical application of color space invariants involves certain difficulties associated with their complex analytical description; moreover, for most practical problems, the high accuracy of the model is redundant. For the practical application of invariants, we propose a simpler approach using natural color sampling in digital printing systems. As an example, the procedure for determining the gray balance for an electrophotographic printing press is given.

The Color Recognition of Jet Fuel Silver Corrosion Images Based on Color Difference Formula

2012 ◽  
Vol 503-504 ◽  
pp. 1033-1036
Author(s):  
Li Ping Tong ◽  
Bin Peng ◽  
Yi Wei Fei
Keyword(s):  
Color Space ◽  
Color Difference ◽  
Recognition System ◽  
Jet Fuel ◽  
Color Spaces ◽  
Object Surface ◽  
Television System ◽  
Color Recognition ◽  
Difference Formula ◽  
Cie Lab

This article introduces the basic theoretical knowledge of the multi-color space and its color difference formula. By research and experiment, it validates that HSV and CIE L * a * b * color space and its corresponding color difference formula, which are used in the color recognition of jet fuel silver corrosion image, and their results are mostly in accordance with the recognition results by the naked eyes. And it also proves the feasibility of these two methods for the color recognition of jet fuel silver corrosion. Silver strip corrosion experiment must be tested as one of jet fuel corrosion detection items in jet fuel accepting, providing and storage process. The examination, whether jet fuel is qualified or not, is mainly due to silver corrosion’s color judgment. For computer visual system, the color is the character of object surface, and it is mankind recognition system to the object surface, light shine and visual condition’s comprehensive effect, and it has important function in the picture’s partition and identifying field. The color that is put up by visible light is continuous, and in order to measure and calculate conveniently, some scholars successively establish more than ten color spaces, which are mainly divided three types, by the HSV color space with RGB, HIS, and Munsell color spaces etc. According to particular application color space, YUV and YIQ and CMY color space are adopted by the television system, and CIE color space then includes CIE, XYZ, Lab and Luv etc. This article comparatively studies representative color space as well as RGB, HIS, CMY, YUV and CIE Lab color spaces, which are used for jet fuel silver strip corrosion image’s color recognition accuracy, and this article finally ensures a kind of color space and color difference formula which are applied to jet fuel silver strip corrosion image’s color recognition.

scholarly journals Investigation of CIE color spaces for differences in color differentiation thresholds in different regions of the color locus

2021 ◽  
Vol 24 (3) ◽  
pp. 107-110
Author(s):  
Leonid D. Lozhkin ◽  
Alexander A. Kuzmenko
Keyword(s):  
Visual Perception ◽  
Significant Role ◽  
Color Space ◽  
Color Difference ◽  
International Commission ◽  
Color Spaces ◽  
Transmission Systems ◽  
Color Coordinates ◽  
Cie Lab

The equidistance of the color space plays a significant role in determining the color difference in color transmission systems. Strictly equal contrasting color spaces can be considered only those color spaces in which equal changes in the visual perception of color are provided with an equal change in the color coordinates in this color space. Currently, the International Commission on Lighting (CIE) has adopted a number of color spaces called equal-contrast. The article presents the results of the study of color spaces adopted by CIE for equal contrast, i.e. on the differences in the thresholds of color differentiation in different areas of the color locus. The article investigated such color spaces as CIE 1931 (RGB), CIE 1931 (x, y), CIE 1960 (u, v), CIE 1976 (u*, v*), CIE LAB (a*, b*).

Analysis of SSIM Based Quality Assessment across Color Channels of Images

2015 ◽  
pp. 1233-1245
Author(s):  
T. Chandrakanth ◽  
B. Sandhya
Keyword(s):  
Image Processing ◽  
Quality Assessment ◽  
Color Space ◽  
Similarity Index ◽  
Human Perception ◽  
Structural Similarity ◽  
Subjective Assessment ◽  
Color Images ◽  
Color Spaces ◽  
Cie Lab

Advances in imaging and computing hardware have led to an explosion in the use of color images in image processing, graphics and computer vision applications across various domains such as medical imaging, satellite imagery, document analysis and biometrics to name a few. However, these images are subjected to a wide variety of distortions during its acquisition, subsequent compression, transmission, processing and then reproduction, which degrade their visual quality. Hence objective quality assessment of color images has emerged as one of the essential operations in image processing. During the last two decades, efforts have been put to design such an image quality metric which can be calculated simply but can accurately reflect subjective quality of human perception. In this paper, the authors evaluated the quality assessment of color images using SSIM (structural similarity index) metric across various color spaces. They experimented to study the effect of color spaces in metric based and distance based quality assessment. The authors proposed a metric using CIE Lab color space and SSIM, which has better correlation to the subjective assessment in a benchmark dataset.

Investigation of the effect of light fastness on the color changes of maps prepared by electrophotographic digital printing

2022 ◽  
Vol 0 (0) ◽  
Author(s):  
Zafer Özomay ◽  
Çağla Koşak Söz ◽  
Sinan Sönmez
Keyword(s):  
The Other ◽  
Digital Printing ◽  
Light Fastness ◽  
Color Changes ◽  
Before And After ◽  
Printing System ◽  
Different Color ◽  
Coated Surfaces ◽  
Electrophotographic Printing ◽  
Effect Of Light

Abstract In this study the prints were made on paper substrates, which were thought as map substrate alternatives, with 3 different surface properties at 1200 dpi by using the electrophotographic printing system. Color and gloss values of the samples were determined both before and after exposure to light for a period of 42 hours to determine the light fastness of the substrate and the print on it. The studies revealed that after the light fastness tests (i) the width of the color universe of the papers with matte surfaces is more than that of the papers with glossy surfaces, (ii) the loss of brightness of woodfree paper is higher than that of the other paper samples and (iii) the print chroma values obtained in woodfree paper is lower than those of the coated surfaces. Moreover, (iv) the delta E 00 {E_{00}} measurements revealed that all paper samples experienced different color losses in different colors, and the most significant differences in these color losses were in magenta and black.

Analysis of SSIM based Quality Assessment across Color Channels of Images

2015 ◽  
Vol 4 (3) ◽  
pp. 30-42 ◽  
Author(s):  
T. Chandrakanth ◽  
B. Sandhya
Keyword(s):  
Image Processing ◽  
Quality Assessment ◽  
Color Space ◽  
Similarity Index ◽  
Human Perception ◽  
Structural Similarity ◽  
Subjective Assessment ◽  
Color Images ◽  
Color Spaces ◽  
Cie Lab

Advances in imaging and computing hardware have led to an explosion in the use of color images in image processing, graphics and computer vision applications across various domains such as medical imaging, satellite imagery, document analysis and biometrics to name a few. However, these images are subjected to a wide variety of distortions during its acquisition, subsequent compression, transmission, processing and then reproduction, which degrade their visual quality. Hence objective quality assessment of color images has emerged as one of the essential operations in image processing. During the last two decades, efforts have been put to design such an image quality metric which can be calculated simply but can accurately reflect subjective quality of human perception. In this paper, the authors evaluated the quality assessment of color images using SSIM (structural similarity index) metric across various color spaces. They experimented to study the effect of color spaces in metric based and distance based quality assessment. The authors proposed a metric using CIE Lab color space and SSIM, which has better correlation to the subjective assessment in a benchmark dataset.

scholarly journals Basic Mathematics of Color Space Invariants

2020 ◽  
Vol 19 ◽  
Keyword(s):  
Mutual Influence ◽  
Color Space ◽  
Three Dimensional ◽  
Analytical Description ◽  
Color Management ◽  
Tone Reproduction ◽  
Initial Color ◽  
Printing Processes ◽  
Cie Lab ◽  
Color Channels

Color management in printing processes has been traditionally based on an analysis of the behavior of tone reproduction curves (TRC) calculated for the initial color channels. The tone curves, as well as, the color channels, are considered separately. This approach does not take into account the mutual influence of colorants when they overlap. We propose replacing two-dimensional tone reproduction curves with three-dimensional gradation trajectories in the CIE Lab metric space. When two colors overlap, one considers the space between two gradation trajectories that forms a gradation surface. These objects are described using the apparatus of differential geometry of spatial curves and surfaces, respectively, and are also invariants of color spaces. In this paper, we offer their analytical description.

Color Space Transformation using Neural Networks

2019 ◽  
Vol 2019 (1) ◽  
pp. 153-158
Author(s):  
Lindsay MacDonald
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Color Space ◽  
Reflectance Spectra ◽  
Network Architectures ◽  
Color Spaces ◽  
Natural Materials ◽  
Space Transformation ◽  
Color Space Transformation

We investigated how well a multilayer neural network could implement the mapping between two trichromatic color spaces, specifically from camera R,G,B to tristimulus X,Y,Z. For training the network, a set of 800,000 synthetic reflectance spectra was generated. For testing the network, a set of 8,714 real reflectance spectra was collated from instrumental measurements on textiles, paints and natural materials. Various network architectures were tested, with both linear and sigmoidal activations. Results show that over 85% of all test samples had color errors of less than 1.0 ΔE2000 units, much more accurate than could be achieved by regression.

scholarly journals The Application of Machine Learning for Cultivar Discrimination of Sweet Cherry Endocarp

Agriculture ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 6
Author(s):  
Ewa Ropelewska
Keyword(s):  
Sweet Cherry ◽  
Color Space ◽  
Geometric Parameters ◽  
Geometric Features ◽  
Color Spaces ◽  
Discriminative Models ◽  
Sweet Cherries ◽  
Rgb Color Space ◽  
Cultivar Discrimination ◽  
Color Channels

The aim of this study was to evaluate the usefulness of the texture and geometric parameters of endocarp (pit) for distinguishing different cultivars of sweet cherries using image analysis. The textures from images converted to color channels and the geometric parameters of the endocarp (pits) of sweet cherry ‘Kordia’, ‘Lapins’, and ‘Büttner’s Red’ were calculated. For the set combining the selected textures from all color channels, the accuracy reached 100% when comparing ‘Kordia’ vs. ‘Lapins’ and ‘Kordia’ vs. ‘Büttner’s Red’ for all classifiers. The pits of ‘Kordia’ and ‘Lapins’, as well as ‘Kordia’ and ‘Büttner’s Red’ were also 100% correctly discriminated for discriminative models built separately for RGB, Lab and XYZ color spaces, G, L and Y color channels and for models combining selected textural and geometric features. For discrimination ‘Lapins’ and ‘Büttner’s Red’ pits, slightly lower accuracies were determined—up to 93% for models built based on textures selected from all color channels, 91% for the RGB color space, 92% for the Lab and XYZ color spaces, 84% for the G and L color channels, 83% for the Y channel, 94% for geometric features, and 96% for combined textural and geometric features.

scholarly journals A Watershed-Segmentation-Based Improved Algorithm for Extracting Cultivated Land Boundaries

2021 ◽  
Vol 13 (5) ◽  
pp. 939
Author(s):  
Yongan Xue ◽  
Jinling Zhao ◽  
Mingmei Zhang
Keyword(s):  
Color Space ◽  
Cultivated Land ◽  
Color Spaces ◽  
Region Merging ◽  
Watershed Segmentation ◽  
Coverage Area ◽  
Time Efficiency ◽  
Image Contrast Enhancement ◽  
Segmentation Accuracy ◽  
Rgb Color Space

To accurately extract cultivated land boundaries based on high-resolution remote sensing imagery, an improved watershed segmentation algorithm was proposed herein based on a combination of pre- and post-improvement procedures. Image contrast enhancement was used as the pre-improvement, while the color distance of the Commission Internationale de l´Eclairage (CIE) color space, including the Lab and Luv, was used as the regional similarity measure for region merging as the post-improvement. Furthermore, the area relative error criterion (δA), the pixel quantity error criterion (δP), and the consistency criterion (Khat) were used for evaluating the image segmentation accuracy. The region merging in Red–Green–Blue (RGB) color space was selected to compare the proposed algorithm by extracting cultivated land boundaries. The validation experiments were performed using a subset of Chinese Gaofen-2 (GF-2) remote sensing image with a coverage area of 0.12 km2. The results showed the following: (1) The contrast-enhanced image exhibited an obvious gain in terms of improving the image segmentation effect and time efficiency using the improved algorithm. The time efficiency increased by 10.31%, 60.00%, and 40.28%, respectively, in the RGB, Lab, and Luv color spaces. (2) The optimal segmentation and merging scale parameters in the RGB, Lab, and Luv color spaces were C for minimum areas of 2000, 1900, and 2000, and D for a color difference of 1000, 40, and 40. (3) The algorithm improved the time efficiency of cultivated land boundary extraction in the Lab and Luv color spaces by 35.16% and 29.58%, respectively, compared to the RGB color space. The extraction accuracy was compared to the RGB color space using the δA, δP, and Khat, that were improved by 76.92%, 62.01%, and 16.83%, respectively, in the Lab color space, while they were 55.79%, 49.67%, and 13.42% in the Luv color space. (4) Through the visual comparison, time efficiency, and segmentation accuracy, the comprehensive extraction effect using the proposed algorithm was obviously better than that of RGB color-based space algorithm. The established accuracy evaluation indicators were also proven to be consistent with the visual evaluation. (5) The proposed method has a satisfying transferability by a wider test area with a coverage area of 1 km2. In addition, the proposed method, based on the image contrast enhancement, was to perform the region merging in the CIE color space according to the simulated immersion watershed segmentation results. It is a useful attempt for the watershed segmentation algorithm to extract cultivated land boundaries, which provides a reference for enhancing the watershed algorithm.

Three-Dimensional Color Gamut Visualization of Digital Output Device Based on ICC Profile

2012 ◽  
Vol 262 ◽  
pp. 36-39 ◽  
Author(s):  
Yun Hui Luo ◽  
Mao Hai Lin
Keyword(s):  
Dimensional Space ◽  
Color Space ◽  
Three Dimensional ◽  
Color Gamut ◽  
Digital Output ◽  
Gamut Mapping ◽  
Output Device ◽  
High Quality Image ◽  
Image Appearance ◽  
Cie Lab

As color gamut of digital output device greatly affects image appearance, accurate and effective gamut description for output device is intensively required for developing high-quality image reproduction technique based on gamut mapping. In this paper, we present a novel method to determine color gamut of output device by using a specific 3D reconstruction technology and device ICC profile. First, we populate the device color space by uniform sampling in the RGB 3-Dimensional space, and convert these sampling points to CMYK color space. Then, we work out the CIE LAB value of these points according to the ICC profile of output device. At last, in CIE LAB color space the boundary of these points is determined by using a gamut boundary descriptor based on Ball-Pivoting Algorithm (BPA) proposed by Bernardini. Compared with the results generated by ICC3D, our proposed method can compute device gamut more efficiently and at the same time give a more accurate gamut description of the output device. It will be help to develop effective gamut mapping algorithms for color reproduction.

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