• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.7
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• pp.1040-1046
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• 2015

This paper introduces GP(Genetic Programming) based color detection model for an object detection of humanoid robot vision. Existing color detection methods have used linear/nonlinear transformation of RGB color-model. However, most of cases have difficulties to classify colors satisfactory because of interference of among color channels and susceptibility for illumination variation. Especially, they are outstanding in degraded images from robot vision. To solve these problems, we propose illumination robust and non-parametric multi-colors detection model using evolution of GP. The proposed method is compared to the existing color-models for various environments in robot vision for real humanoid Nao.

• Journal of Biosystems Engineering
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• v.32 no.3
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• pp.160-165
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• 2007

This study was conducted to evaluate beef using a color machine vision system. The machine vision system has an advantage to measure larger area than a colorimeter and also could measure other quality factors like distribution of fats. However, the machine vision measurement is affected by system components. To measure the beef color with the machine vision system, the effect of color balancing control was tested and calibration model was developed. Neural network for color calibration which learned reference color patches showed a high correlation with colorimeter in L*a*b* coordinates and had an adaptability at various measurement environments. The trained network showed a very high correlation with the colorimeter when measuring beef color.

• Agricultural and Biosystems Engineering
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• v.3 no.1
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• pp.35-43
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• 2002

The spectral color resolution of an image is very important in color image analysis. Two factors influencing the spectral color resolution of an image are illumination intensity and lens aperture for a selected vision system. An optimal combination of illumination intensity and lens aperture for color image analysis was determined in the study. The method was based on a model of dynamic range defined as the absolute difference between digital values of selected foreground and background color in the image. The role of illumination intensity in machine vision was also described and a computer program for simulating the optimal combination of two factors was implemented for verifying the related algorithm. It was possible to estimate the non-saturating range of the illumination intensity (input voltage in the study) and the lens aperture by using a model of dynamic range. The method provided an optimal combination of the illumination intensity and the lens aperture, maximizing the color resolution between colors of interest in color analysis, and the estimated color resolution at the combination for a given vision system configuration.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.1
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• pp.32-39
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• 2004

The color-based vision systems have been used to recognize our team robots, the opponent team robots and a ball in the robot soccer system. The color-based vision systems have the difficulty in that they are very sensitive to color variations brought by brightness changes. In this paper, a neural network trained with data obtained from various illumination conditions is used to classify colors in the modified YUV color space for the robot soccer vision system. For this, a new method to measure brightness is proposed by use of a color card. After the neural network is constructed, a look-up-table is generated to replace the neural network in order to reduce the computation time. Experimental results show that the proposed color classification method is robust under illumination variations.

• Journal of Korean Ophthalmic Optics Society
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• v.10 no.4
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• pp.329-337
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• 2005

This study investigated prevalence of color vision loss different from children's residence. The study subjects are 3 to 6 grade's children of elementary school in four areas. The blood lead and urinary mercury were analysed using Atomic Absorption Spectroscopy. All of participations' blood lead and urine mercury concentration were below suggested level of concern such as criteria by CDC and ATSDR. Color vision was assessed by the Lanthony D-15 desaturated panel. Color vision loss was quantitatively established by the Color Confusion Index (CCI) and qualitatively classified by type of acquired dyschromatopsia according to Verriest's classification. The prevalence of color vision loss and CCI value for children in industrial area was significantly higher than other areas(p<0.05). However blood lead and urinary mercury concentration level was not correlated to the color vision loss. Therefore we believed that other environmental neurotoxic substance except metal had an effects on color vision loss for children in industrial area.

• Architectural research
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• v.18 no.3
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• pp.83-90
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• 2016

Senescent effects are the gradual deterioration of function caused by biological aging. Senescent effects on color vision are not clearly understood even after considerable researches. Part of the reason is that the color vision is a complex phenomenon resulting from various factors such as organic systems, and the physical (neuro-optical) and the psychological (experiential) processes of color perception. We performed a field experiment on color perceptional differences due to aging vision. Our experiment was applied to two different groups in South Korea: an experimental group (46 subjects of over the age of 61 years) and a control group (49 subjects in their twenties). The experimental tools are comprised of (1) six gradual yellowing detector board (40%, 50%, 60%, 70%, 80%, 90%); (2) pairs of vivid-strong, vivid-deep, grayish-deep, deep-dull, and bright-light tones of Blue (B) and Purple (P) colors; (3) Red (R), Yellow (Y), Green (G), Blue (B), and Purple (P) colors of dull-tones and pale-tones; and (4) a questionnaire on the semantic differential scales of the color images and color differences. A diagnosis system of gradual yellow vision, developed by the authors for this study, was adapted to generate the color detecting boards. The results are as follows. (1) There are significant differences between the two groups in detecting colors that simulate 40% and 50% of yellow vision. (2) As to the color difference detecting ability between similar tones, the experimental group shows difficulties in pairs of vivid-strong tones and deep-dull tones of the B color. And (3), the emotional responses to the dull tone and the pale tone are not stable in the red, the yellow, blue, and purple. Thus, we empirically demonstrate the specific differences in color perception between the old and young groups.

• Journal of Korean Ophthalmic Optics Society
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• v.16 no.3
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• pp.307-312
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• 2011

Purpose: To investigate the prevalence of congenital and age-related color vision deficiencies over a wide range of ages among residents in two urban communities of Kyeonggi-Do. Methods: A total of 935 subjects, consisting of 452 males and 483 females, participated in this study. Lanthony D-15 desaturated panels test were used to assess color vision. Results: Prevalence of color vision deficiency was 4.81% for total, 6.64% for males and 3.11% for females. Congenital color vision deficiency was 3.54% for males and 0.41% for females. Tritan deficiency, which was the post-natal age-related, was 2.99% (3.32% for males, and 2.69% for females). Conclusions: The result imply that color vision deficiencies is influenced by age. As an age-related color vision deficiencies, Tritan is most frequently found in the age group over 50.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.836-841
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• 2004

This paper describes ASIC design for brightness revision control, A LED Pixel Matrix (LPM) design and LPM in natural color LED vision. A designed chip has 256 levels of gradation correspond to each Red, Green, Blue LED pixel respectively, which have received 8bit image data. In order to maintain color uniformity by reducing the original rank error of LED, we adjusted the specific character value 'a' and brightness revision value 'b' to pixel unit, module unit and LED vision respectively by brightness characteristic function with 'Y=aX+b'. In this paper, if designed custom chip and brightness revision control method are applied to manufacturing of natural color LED vision, we can obtain good quality of image. Furthermore, it may decrease the cost for manufacturing LED vision or installing the plants.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.4
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• pp.272-280
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• 2015

This paper proposes color databases that can be used for various purposes for people with a color vision deficiency (CVD). The purpose of this paper is to group colors within the sRGB gamut into the CIE $L^*a^*b^*$ color space using the Brettel algorithm to simulate the representative colors of each group into colors visible to people with a CVD, and to establish a confusion line database by comparing colors that might cause confusion for people with different types of color vision deficiency. The validity of the established confusion lines were verified by using an Ishihara chart. The different colors that confuse those with a CVD in an Ishihara chart are located in the same confusion line database for both protanopia and deutanopia. Instead of the 3D RGB color space, we have grouped confusion colors to the CIE $L^*a^*b^*$ space coordinates in a more distinctive and intuitive manner, and can establish a database of colors that can be perceived by people with a CVD more accurately. Editor - Highlight - Do these changes reflect the intended meaning? If not, please rephrase as intended.

• Journal of Biosystems Engineering
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• v.33 no.6
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• pp.446-452
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• 2008

Machine vision system was used for analyzing leaf color disorders of tomato plants in a greenhouse. From the day when a few leave of tomato plants had started to wither, a series of images were captured by 4 times during 14 days. Among several color image spaces, Saturation frame in HSI color space was adequate to eliminate a background and Hue frame was good to detect infected disease area and tomato fruits. The processed image ($G{\sqcup}b^*$ image) by OR operation between G frame in RGB color space and $b^*$ frame in $La^*b^*$ color space was useful for image segmentation of a plant canopy area. This study calculated a ratio of the infected area to the plant canopy and manually analyzed leaf color disorders through an image segmentation for Hue frame of a tomato plant image. For automatically analyzing plant leave disease, this study selected twenty-seven color patches on the calibration bars as the corresponding to leaf color disorders. These selected color patches could represent 97% of the infected area analyzed by the manual method. Using only ten color patches among twenty-seven ones could represent over 85% of the infected area. This paper showed a proposed machine vision system may be effective for evaluating various leaf color disorders of plants growing in a greenhouse.