Study on the basic color and color of camouflage paint in computer color matching

2019 ◽  
Author(s):  
Ju Jianjun ◽  
Liu Heng ◽  
Hao Xu ◽  
Tian Jiyao ◽  
Yang Xin
Keyword(s):  
Color Matching ◽  
Basic Color

Preliminary Study on Application of Computer Color Matching Technique for Wood Dyeing

2011 ◽  
Vol 474-476 ◽  
pp. 1228-1232 ◽  
Author(s):  
Wei Liu ◽  
Zhi Ming Yu ◽  
Wan Zhao Li
Keyword(s):  
Visual Perception ◽  
Wood Species ◽  
Black Walnut ◽  
Color Matching ◽  
Human Visual Perception ◽  
Fast Growing ◽  
Matching Technique ◽  
Basic Color ◽  
Preliminary Study

Wood dyeing requires a non-subjective, repeatable method for determining the color testing and matching. Previously published method used human visual perception to determine the percent of dyestuffs. In this study, computer color matching technique was applied into the dyeing of fast growing wood for the imitation of precious wood species. The process includes measuring the color of wood samples, determining dyeset, preparing and measuring basic color samples, establishing a basic database, calculating and correcting recipes. The recipe of black walnut provided by the system was as follows: acid yellow 2G 0.19%, acid green 0.59%, acid red B 0.29%, with the chromatic difference 0.12%. It could be concluded that dyeing with computer color matching technique allows for a faster, less subjective and easily repeatable procedure that is superior to simple human visual perception.

Change of color appearance due to extremely high light level: corresponding colors under 100 and 3000 cd/m2

2019 ◽  
Vol 2019 (1) ◽  
pp. 320-325 ◽  
Author(s):  
Wenyu Bao ◽  
Minchen Wei
Keyword(s):  
Light Level ◽  
Limited Range ◽  
High Light ◽  
Color Preference ◽  
Color Appearance ◽  
Appearance Model ◽  
Color Matching ◽  
Light Levels ◽  
Appearance Models ◽  
Psychophysical Study

Great efforts have been made to develop color appearance models to predict color appearance of stimuli under various viewing conditions. CIECAM02, the most widely used color appearance model, and many other color appearance models were all developed based on corresponding color datasets, including LUTCHI data. Though the effect of adapting light level on color appearance, which is known as "Hunt Effect", is well known, most of the corresponding color datasets were collected within a limited range of light levels (i.e., below 700 cd/m2), which was much lower than that under daylight. A recent study investigating color preference of an artwork under various light levels from 20 to 15000 lx suggested that the existing color appearance models may not accurately characterize the color appearance of stimuli under extremely high light levels, based on the assumption that the same preference judgements were due to the same color appearance. This article reports a psychophysical study, which was designed to directly collect corresponding colors under two light levels— 100 and 3000 cd/m2 (i.e., ≈ 314 and 9420 lx). Human observers completed haploscopic color matching for four color stimuli (i.e., red, green, blue, and yellow) under the two light levels at 2700 or 6500 K. Though the Hunt Effect was supported by the results, CIECAM02 was found to have large errors under the extremely high light levels, especially when the CCT was low.

Evaluation of Stable Morphological Traits in Soybean Collection Samples for Determination of Standard Varieties

2020 ◽  
pp. 67-77
Keyword(s):  
Seed Coat ◽  
Leaf Size ◽  
Flower Color ◽  
The Other ◽  
Main Stem ◽  
Complete Evaluation ◽  
Varietal Identification ◽  
Basic Color ◽  
Dark Color ◽  
Generative Organs

For identification of varieties, it is desirable to use genetically predetermined traits that are decisive for the varietal identification of the distinguishing characteristics of the varieties production and new genotypes for selection. The presence a complete evaluation of the selection samples a particular crop is the basis for the formation of informative databases characteristics the varieties of standards used in plant examination to determine the level of expression a characteristic particular genotype according to the code of their manifestation. For the 20 traits we used to identify, we identified 6 least volatile, highly trait-stable traits over the years of study to identify. These are: “coloring of the pubescence of the main stem”, “the size of the lateral leaf”, “the intensity of green leaf color”, “flower color”, “the intensity of brown bean color”, “basic color of the seed coat”. The other 14 traits are highly variable and unstable among varieties, but may be significant under certain conditions. According to the results of the research we have determined the conformity of the collection varieties by code graduation. In the study, we selected varieties with corresponding codes of attributes of the reference varieties the UPOV technique. On the basic of the color the pubescence of the main stem, 36% varieties are with grey stem pubescence. Among the standards: Apache, Alaric, Talon according to the grey color of the pubescence, we identified varieties Zolotysta, Ozzie, Diona. The 2947 564/84, Stepnaya-90, Knyazhna. The lateral leaf size is a sign that affects the increase in green mass of plants and subsequently on productivity. Graduation of the sign small size of leaf had varieties: Zuma, Ksenya; middle – Heinong 37, Yuh-30; large – 2947 564/84, Vinni, DSS 2504. The following is a sign of the intensity of leaf plate, which is divided by gradation into light, moderate and dark. Among our samples with a light degree of color, we can distinguish Diona, Sribna Ruta, and Zuma. For varieties with moderate gradation of color are selected: Perlyna, 93/99, Knyazhna. To the dark color of the leaf plate we attributed the varieties: Stepnaya-90, Ozzie. Among the varieties we studied of the basics of flower color 37% varieties are with a white flower, and 63% with a purple. According to the varieties of standards: Chandor, Cresir, Toreador to the white color of the flower we attributed varieties Knyazhna, Ozzie, Zolotysta. With the purple color of the flower we have selected varieties: 93/99, Zhemchuzhna, Heinong 37. On the basis of the intensity of brown color bean, which characterizes the generative organs of the plant, is divided into weak, moderate and strong, but the other identifiers there are gradations: sandy, gray, light brown, brown and dark brown, so we decided what would be better identify by color gradation. To the sandy color of the beans we attributed varieties Perlyna, Yuh-30; gray – Sribna Ruta; light brown – Kobza, Knyazhna; brown – Ksenya; dark brown – Zhemchuzhna, Vinni. Important features that identify the description of varieties include basic color of the seed coat, which affects the taste of the seeds. In particular, the seeds are divided by color into yellow – Kobza, Yuh-30; yellow-green – Vinni, Luch Nadezhdy; green – Heorhina; light brown – 2947 564/84, brown – DSS 2504; dark brown – 2974 YS-24 and black color – not detected. Following the results of the previous collection of soybean varieties from the morphological sings of vegetative, generative organs of plants, it was possible to identify varieties with stable manifestation of standard identifying sings of soybean. Collection varieties with one standard characteristics: Heinong 37, Luch Nadezhdy, DSS 2504, 2974 YS-24; two signs: Zolotysta, Diona, Stepnaya-90, Zuma, Ksenya, Heorhina, Sribna Ruta, Perlyna, 93/99, Zhemchuzhna; three signs: Ozzie, 2947 564/84, Yuh-30, Vinni, Knyazhna.

Visual effect and color matching of dynamic image webpage design

2021 ◽  
Author(s):  
Lungwen Kuo ◽  
Tsuiyueh Chang ◽  
Chih‐Chun Lai
Keyword(s):  
Color Matching ◽  
Visual Effect ◽  
Dynamic Image

Research on color matching of LED backlight for large-color-gamut LCD application

2007 ◽  
Author(s):  
Meng Liang ◽  
Manning Fan ◽  
Debo Guo ◽  
Guangyi Liu ◽  
Guohong Wang ◽  
...  
Keyword(s):  
Color Matching ◽  
Color Gamut ◽  
Led Backlight

Color matching on natural substrates in cuttlefish, Sepia officinalis

2008 ◽  
Vol 194 (6) ◽  
pp. 577-585 ◽  
Author(s):  
Lydia M. Mäthger ◽  
Chuan-Chin Chiao ◽  
Alexandra Barbosa ◽  
Roger T. Hanlon
Keyword(s):  
Sepia Officinalis ◽  
Color Matching

Algorithm of Color Detection for Moving Video Objects Based on Mode Matching

2012 ◽  
Vol 239-240 ◽  
pp. 1000-1003
Author(s):  
Zhao Quan Cai ◽  
Hui Hu ◽  
Tao Xu ◽  
Wei Luo ◽  
Yi Cheng He
Keyword(s):  
Background Subtraction ◽  
Moving Objects ◽  
Color Matching ◽  
Human Beings ◽  
Current Image ◽  
Color Recognition ◽  
Recognition Ability ◽  
Color Identification ◽  
The Difference ◽  
Background Image

It is urgent to study how to effectively identify color of moving objects from the video in the information era. In this paper, we present the color identification methods for moving objects on fixed camera. One kind of the methods is background subtraction that recognizes the foreground objects by compare the difference of pixel luminance between the current image and the background image at the same coordinates. Another kind is based on the statistics of HSV color and color matching which makes the detection more similar to the color identification of the human beings. According to the experiment results, after the completion of the background modelling, our algorithm of background subtraction, statistics of the HSV color and the color matching have strong color recognition ability on the moving objects of video.

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