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In this issue

In this issue Does your preference for certain colors change when you are looking at a small color patch versus when you are looking at an object or the wall of a room? In our first article “Object Color Preferences” Karen B. Schloss, Eli D. Strauss, and Steve Palmer report on four experiments examining this topic. They compared preferences of observers when the observers are looking at colored squares without any context, the observers preferences when looking at the color of imagined objects, images of color objects, and actual objects. And finally in their fourth experiment they studied the possibility that object color preferences are related to the degree to which colors help objects fulfill particular functions. Throughout history, humans primarily became accustomed to looking at objects and their colors in daylight. When we see objects in a different illumination, say indoors with tungsten light, our visual system automatically adjusts the perception so the colors appear more as they do under daylight. This automatic adaptation to the illumination is called color constancy. Other image capture systems need to include an adjustment for the illumination in order to render colors as we see them. While many techniques have been developed to accomplish this transform, in our next article, Claudio Oleari, Fernando Fermi, and Andrej Učakar present a “Digital Image Color Conversion between Different Illuminants by Perfect Color‐Constancy Actuation in a Color‐Vision Model based on the OSA‐UCS System.” While we are considering perception of colors, let us also consider black. As colors become darker and darker they approach black, but does the color itself have an effect on how black the perception appears? And if it does, which is the preferred black? In “The Effect of Hue Angle on the Perception of Blackness Using Munsell Samples,” J. Reid Clonts Haslup, David Hicks, and Renzo Shamey attempt answer these questions. They found that while a single preferred hue angle could not be determined, the bluish or greenish blacks were definitely considered blacker than yellowish (brownish) or reddish blacks. A large group of researchers from three continents join together for our next article. Manuel Melgosa Latorre, David Alman, Martina Grosman, Luis Gómez‐Robledo, Alain Tremeau, Guihua Cui, Pedro Garcia, Daniel Molini, Changjun Li, and M. Ronnier Luo provide a “Practical Demonstration of the CIEDE2000 Corrections to CIELAB Using a Small Set of Sample Pairs.” When the CIE was working to develop an improved color difference metric, five areas in which CIELAB had particular problems were identified. Following the publication of the CIEDE2000 color difference formula, a set of 10 color‐difference pairs were produced to illustrate the improvement of CIEDE2000 over CIELAB. After describing the pairs, the authors go on to describe two visual experiments with the 10 pairs and report a decrease of STRESS values by 20 when using CIEDE2000 compared to CIELAB in these experiments. Giulia Paggetti and Gloria Menegaz, have been studying color naming in Italian. Their article the “Exact location of consensus and consistency colors in the OSA‐UCS for the Italian language,” in this issue is a follow‐up to an article published in Attention, Perception, and Psychophysics in 2011. In the current article, they report the exact position of focal colors, centroids, and consensus colors of the Italian language in the Optical Society of America—Uniform Color Scales (OSA‐UCS). They go on to compare their results with the findings of Boynton and Olson. Their results indicate a strong agreement on the location of linguistic color terms, except for blue. In the series of articles by Antal Nemcsics entitled “Experimental determination of laws of color harmony,” he has described evaluations made of artwork in traditional settings for observers viewing artwork in daylight or museum lighting. However, experiments were also conducted in the situation where the observers were in the dark and adapted to dark before the observations. In “Part 7: Experiments carried out with eyes adapted to light and dark,” Prof. Nemcsics joins with Jenö Takács to report on the comparison of observations with different adaptation and viewing conditions, and they conclude that the two observation conditions lead to very different results. Thus the dark simulated conditions cannot be used for judgments of color harmony in daylight or museum conditions and need their own set of rules for color harmony. The color of fabrics may be produced in different ways. One is by dying the fabric, another way is by weaving colored threads to form the fabric. The effects are different and the color and quality control are also different. In our next article, Ruru Pan, Jihong Liu, and Weidong Gao describe “Automatic Detection of Single‐system‐mélange Color Fabric Density with FCM Algorithm.” In this article, the authors discuss a method for inspecting the linear density of threads in a single‐system‐mélange color fabric, in which there is the same color warps and different color wefts. They propose a Fuzzy C‐Means Clustering Method (FCM) algorithm to classify the colors in CIELAB color space. Our final article in this issue is “A Study of Color Differences in Women's Ready‐to‐wear Collections from World Fashion Cities: Intensive study of the Fall/Winter 2010 Collections from New York, London, Milan and Paris.” Color is a key factor in shopping for clothing. The colors in fashion in women's clothing change seasonally and yearly, and perhaps geographically. Youngrim Koh and Joo Hyeon Lee used the Fall/Winter collection from 2010 to study and analyze these changes. Analyzing the differences in these four collections of this period, the article suggests a new objective method in the area of color trend research. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Color Research & Application Wiley

In this issue

Color Research & Application , Volume 38 (6) – Dec 1, 2013
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Publisher
Wiley
Copyright
Copyright © 2013 Wiley Periodicals, Inc.
ISSN
0361-2317
eISSN
1520-6378
DOI
10.1002/col.21842
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Abstract

Does your preference for certain colors change when you are looking at a small color patch versus when you are looking at an object or the wall of a room? In our first article “Object Color Preferences” Karen B. Schloss, Eli D. Strauss, and Steve Palmer report on four experiments examining this topic. They compared preferences of observers when the observers are looking at colored squares without any context, the observers preferences when looking at the color of imagined objects, images of color objects, and actual objects. And finally in their fourth experiment they studied the possibility that object color preferences are related to the degree to which colors help objects fulfill particular functions. Throughout history, humans primarily became accustomed to looking at objects and their colors in daylight. When we see objects in a different illumination, say indoors with tungsten light, our visual system automatically adjusts the perception so the colors appear more as they do under daylight. This automatic adaptation to the illumination is called color constancy. Other image capture systems need to include an adjustment for the illumination in order to render colors as we see them. While many techniques have been developed to accomplish this transform, in our next article, Claudio Oleari, Fernando Fermi, and Andrej Učakar present a “Digital Image Color Conversion between Different Illuminants by Perfect Color‐Constancy Actuation in a Color‐Vision Model based on the OSA‐UCS System.” While we are considering perception of colors, let us also consider black. As colors become darker and darker they approach black, but does the color itself have an effect on how black the perception appears? And if it does, which is the preferred black? In “The Effect of Hue Angle on the Perception of Blackness Using Munsell Samples,” J. Reid Clonts Haslup, David Hicks, and Renzo Shamey attempt answer these questions. They found that while a single preferred hue angle could not be determined, the bluish or greenish blacks were definitely considered blacker than yellowish (brownish) or reddish blacks. A large group of researchers from three continents join together for our next article. Manuel Melgosa Latorre, David Alman, Martina Grosman, Luis Gómez‐Robledo, Alain Tremeau, Guihua Cui, Pedro Garcia, Daniel Molini, Changjun Li, and M. Ronnier Luo provide a “Practical Demonstration of the CIEDE2000 Corrections to CIELAB Using a Small Set of Sample Pairs.” When the CIE was working to develop an improved color difference metric, five areas in which CIELAB had particular problems were identified. Following the publication of the CIEDE2000 color difference formula, a set of 10 color‐difference pairs were produced to illustrate the improvement of CIEDE2000 over CIELAB. After describing the pairs, the authors go on to describe two visual experiments with the 10 pairs and report a decrease of STRESS values by 20 when using CIEDE2000 compared to CIELAB in these experiments. Giulia Paggetti and Gloria Menegaz, have been studying color naming in Italian. Their article the “Exact location of consensus and consistency colors in the OSA‐UCS for the Italian language,” in this issue is a follow‐up to an article published in Attention, Perception, and Psychophysics in 2011. In the current article, they report the exact position of focal colors, centroids, and consensus colors of the Italian language in the Optical Society of America—Uniform Color Scales (OSA‐UCS). They go on to compare their results with the findings of Boynton and Olson. Their results indicate a strong agreement on the location of linguistic color terms, except for blue. In the series of articles by Antal Nemcsics entitled “Experimental determination of laws of color harmony,” he has described evaluations made of artwork in traditional settings for observers viewing artwork in daylight or museum lighting. However, experiments were also conducted in the situation where the observers were in the dark and adapted to dark before the observations. In “Part 7: Experiments carried out with eyes adapted to light and dark,” Prof. Nemcsics joins with Jenö Takács to report on the comparison of observations with different adaptation and viewing conditions, and they conclude that the two observation conditions lead to very different results. Thus the dark simulated conditions cannot be used for judgments of color harmony in daylight or museum conditions and need their own set of rules for color harmony. The color of fabrics may be produced in different ways. One is by dying the fabric, another way is by weaving colored threads to form the fabric. The effects are different and the color and quality control are also different. In our next article, Ruru Pan, Jihong Liu, and Weidong Gao describe “Automatic Detection of Single‐system‐mélange Color Fabric Density with FCM Algorithm.” In this article, the authors discuss a method for inspecting the linear density of threads in a single‐system‐mélange color fabric, in which there is the same color warps and different color wefts. They propose a Fuzzy C‐Means Clustering Method (FCM) algorithm to classify the colors in CIELAB color space. Our final article in this issue is “A Study of Color Differences in Women's Ready‐to‐wear Collections from World Fashion Cities: Intensive study of the Fall/Winter 2010 Collections from New York, London, Milan and Paris.” Color is a key factor in shopping for clothing. The colors in fashion in women's clothing change seasonally and yearly, and perhaps geographically. Youngrim Koh and Joo Hyeon Lee used the Fall/Winter collection from 2010 to study and analyze these changes. Analyzing the differences in these four collections of this period, the article suggests a new objective method in the area of color trend research.

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Color Research & Application – Wiley

Published: Dec 1, 2013

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