The Experts below are selected from a list of 306 Experts worldwide ranked by ideXlab platform
Jorge Leon - One of the best experts on this subject based on the ideXlab platform.
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Color Measurement in l a b units from rgb digital images
Food Research International, 2006Co-Authors: Katherine Leon, Domingo Mery, Franco Pedreschi, Jorge LeonAbstract:Abstract The superficial appearance and Color of food are the first parameters of quality evaluated by consumers, and are thus critical factors for acceptance of the food item by the consumer. Although there are different Color spaces, the most used of these in the measuring of Color in food is the L ∗ a ∗ b ∗ Color space due to the uniform distribution of Colors, and because it is very close to human perception of Color. In order to carry out a digital image analysis in food, it is necessary to know the Color measure of each pixel on the surface of the food item. However, there are at present no commercial L ∗ a ∗ b ∗ Color measures in pixels available because the existing commercial Colorimeters generally measure small, non-representative areas of a few square centimeters. Given that RGB digital cameras obtain information in pixels, this article presents a computational solution that allows the obtaining of digital images in L ∗ a ∗ b ∗ Color units for each pixel of the digital RGB image. This investigation presents five models for the RGB → L ∗ a ∗ b ∗ conversion and these are: linear, quadratic, gamma, direct, and neural network. Additionally, a method is suggested for estimating the parameters of the models based on a minimization of the mean absolute error between the Color Measurements obtained by the models, and by a commercial Colorimeter for uniform and homogenous surfaces. In the evaluation of the performance of the models, the neural network model stands out with an error of only 0.93%. On the basis of the construction of these models, it is possible to find a L ∗ a ∗ b ∗ Color measuring system that is appropriate for an accurate, exacting and detailed characterization of a food item, thus improving quality control and providing a highly useful tool for the food industry based on a Color digital camera.
Katherine Leon - One of the best experts on this subject based on the ideXlab platform.
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Color Measurement in l a b units from rgb digital images
Food Research International, 2006Co-Authors: Katherine Leon, Domingo Mery, Franco Pedreschi, Jorge LeonAbstract:Abstract The superficial appearance and Color of food are the first parameters of quality evaluated by consumers, and are thus critical factors for acceptance of the food item by the consumer. Although there are different Color spaces, the most used of these in the measuring of Color in food is the L ∗ a ∗ b ∗ Color space due to the uniform distribution of Colors, and because it is very close to human perception of Color. In order to carry out a digital image analysis in food, it is necessary to know the Color measure of each pixel on the surface of the food item. However, there are at present no commercial L ∗ a ∗ b ∗ Color measures in pixels available because the existing commercial Colorimeters generally measure small, non-representative areas of a few square centimeters. Given that RGB digital cameras obtain information in pixels, this article presents a computational solution that allows the obtaining of digital images in L ∗ a ∗ b ∗ Color units for each pixel of the digital RGB image. This investigation presents five models for the RGB → L ∗ a ∗ b ∗ conversion and these are: linear, quadratic, gamma, direct, and neural network. Additionally, a method is suggested for estimating the parameters of the models based on a minimization of the mean absolute error between the Color Measurements obtained by the models, and by a commercial Colorimeter for uniform and homogenous surfaces. In the evaluation of the performance of the models, the neural network model stands out with an error of only 0.93%. On the basis of the construction of these models, it is possible to find a L ∗ a ∗ b ∗ Color measuring system that is appropriate for an accurate, exacting and detailed characterization of a food item, thus improving quality control and providing a highly useful tool for the food industry based on a Color digital camera.
Zhen Liu - One of the best experts on this subject based on the ideXlab platform.
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Optimization of the method for Color Measurement of printing on holographic paper
Color Research & Application, 2011Co-Authors: Xin Guo Huang, Xiao Xia Wan, Zhen LiuAbstract:Color is one of the most important quality control parameters for printing, but there is no applicable Color Measurement method for printing on holographic paper. The aim of this study was to analyze the reason why current instruments are unable to provide accurate Color Measurement for holographic paper printing and find a way to solve the problem. Diffuse geometry instrument was proved to be more suitable than directional geometry instrument for holographic paper printing. Variations in the measured Color coordinates due to holograph patterns were observed by measuring four types of holographic papers before and after printing. The distribution uniformity and the area of holographic patterns were considered as the main factors that influence Measurement repeatability and consistency. By using d:8° geometry instrument in specular component included (SCI) mode and large circular measured area, Measurements at two angles of the same point and averaging, or Measurements at three different positions and averaging were proved to improve the Measurement repeatability on a single point and Measurement consistency on a single sheet of holographic paper. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2013
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Uncertainty Evaluation of Spectral Color Measurement
Advanced Materials Research, 2010Co-Authors: Xiao Xia Wan, Xin Guo Huang, Zhen LiuAbstract:Uncertainty evaluation of spectral Color Measurement is the best method of evaluation of Color Measurement result’s quality. Firstly type A and type B uncertainty of spectral reflectance are analyzed based on different uncertainty's sources, secondly uncertainty of chromaticity parameters are calculated based on spectral reflectance’s uncertainty. Lastly practicability of uncertainty evaluation of spectral Color Measurement is proved by experiments.
William D. Browning - One of the best experts on this subject based on the ideXlab platform.
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Use of shade guides for Color Measurement in tooth-bleaching studies.
Journal of Esthetic and Restorative Dentistry, 2003Co-Authors: William D. BrowningAbstract:Several different methods are used to measure tooth Color in bleaching studies. The ADA Acceptance Program Guidelines for Home Use Tooth Whitening Products specify the use of a value-oriented shade guide and/or electronic Color Measurement devices. Since people perceive Color differently, shade guides are a subjective measure. Differences between raters and by the same rater are well documented in the dental literature. The purposes of this article will be to discuss the advantages and disadvantages using shade guides to measure Color change related to tooth whitening, and to evaluate the correlation of data gathered from the use of shade guides to electronic Color Measurement devices. Using an order published by the manufacturer, both the TRUBYTE® Bioform and Vita Classical guides can be arranged by value. A study by O'Brien demonstrated however, that the order is flawed and the change in brightness from tab to tab varies greatly. Despite these disadvantages, a review of data from several clinical trials demonstrates that Vita Classical shade guide data is consistent with data gathered using electronic Color Measurements. Furthermore, the O'Brien data can be used to make both these guides better Measurement systems. The ADA Certification program standards define the degree of overall Color change that should be considered clinically important. This issue is as critical as the Measurement system used. Reporting Color changes that are neither detectable to the human eye nor considered by the public to be important offers the profession little usable information. Given that any standard for Color change during bleaching must relate to the abilities of the human eye, it is the conclusion of the author that shade guides should remain a critical element of any bleaching study. CLINICAL SIGNIFICANCE Clinicians are frequently exposed to reports of bleaching agents that have been shown to result in a change of 6, 7, 8, etc., tabs. Without understanding the limitations of the shade guide used, reports of a specific shade tab change are of little use and may actually be misleading.
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Use of shade guides for Color Measurement in tooth-bleaching studies.
Journal of esthetic and restorative dentistry : official publication of the American Academy of Esthetic Dentistry ... [et al.], 2003Co-Authors: William D. BrowningAbstract:Several different methods are used to measure tooth Color in bleaching studies. The ADA Acceptance Program Guidelines for Home Use Tooth Whitening Products specify the use of a value-oriented shade guide and/or electronic Color Measurement devices. Since people perceive Color differently, shade guides are a subjective measure. Differences between raters and by the same rater are well documented in the dental literature. The purposes of this article will be to discuss the advantages and disadvantages using shade guides to measure Color change related to tooth whitening, and to evaluate the correlation of data gathered from the use of shade guides to electronic Color Measurement devices. Using an order published by the manufacturer, both the TRUBYTE Bioform and Vita Classical guides can be arranged by value. A study by O'Brien demonstrated however, that the order is flawed and the change in brightness from tab to tab varies greatly. Despite these disadvantages, a review of data from several clinical trials demonstrates that Vita Classical shade guide data is consistent with data gathered using electronic Color Measurements. Furthermore, the O'Brien data can be used to make both these guides better Measurement systems. The ADA Certification program standards define the degree of overall Color change that should be considered clinically important. This issue is as critical as the Measurement system used. Reporting Color changes that are neither detectable to the human eye nor considered by the public to be important offers the profession little usable information. Given that any standard for Color change during bleaching must relate to the abilities of the human eye, it is the conclusion of the author that shade guides should remain a critical element of any bleaching study. Clinicians are frequently exposed to reports of bleaching agents that have been shown to result in a change of 6, 7, 8, etc., tabs. Without understanding the limitations of the shade guide used, reports of a specific shade tab change are of little use and may actually be misleading.
Domingo Mery - One of the best experts on this subject based on the ideXlab platform.
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Color Measurement in l a b units from rgb digital images
Food Research International, 2006Co-Authors: Katherine Leon, Domingo Mery, Franco Pedreschi, Jorge LeonAbstract:Abstract The superficial appearance and Color of food are the first parameters of quality evaluated by consumers, and are thus critical factors for acceptance of the food item by the consumer. Although there are different Color spaces, the most used of these in the measuring of Color in food is the L ∗ a ∗ b ∗ Color space due to the uniform distribution of Colors, and because it is very close to human perception of Color. In order to carry out a digital image analysis in food, it is necessary to know the Color measure of each pixel on the surface of the food item. However, there are at present no commercial L ∗ a ∗ b ∗ Color measures in pixels available because the existing commercial Colorimeters generally measure small, non-representative areas of a few square centimeters. Given that RGB digital cameras obtain information in pixels, this article presents a computational solution that allows the obtaining of digital images in L ∗ a ∗ b ∗ Color units for each pixel of the digital RGB image. This investigation presents five models for the RGB → L ∗ a ∗ b ∗ conversion and these are: linear, quadratic, gamma, direct, and neural network. Additionally, a method is suggested for estimating the parameters of the models based on a minimization of the mean absolute error between the Color Measurements obtained by the models, and by a commercial Colorimeter for uniform and homogenous surfaces. In the evaluation of the performance of the models, the neural network model stands out with an error of only 0.93%. On the basis of the construction of these models, it is possible to find a L ∗ a ∗ b ∗ Color measuring system that is appropriate for an accurate, exacting and detailed characterization of a food item, thus improving quality control and providing a highly useful tool for the food industry based on a Color digital camera.