• Journal of Biosystems Engineering
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• v.17 no.2
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• pp.123-131
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• 1992

This study was carried out to analyze the characteristics of the color computer vision to discriminate apple surface color for grading apples by their color. It was intended to develop the techniques to be able to discriminate apple color as precisely as human inspection does. For the purpose, discrimination of apple color by human inspection was checked and justified ; various illumination methods for various frames of the color computer vision(R, G, B, H, S and I frames) were tested ; and several methods to analyze image informations of the color computer vision were tried to evaluate their ability to discriminate apple color close to the human inspection.

• 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.22 no.1
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• pp.30-40
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• 1997

A computer vision system was built to automatically grade the leaf tobacco. A color image processing algorithm was developed to extract shape, color and texture features. An improved back propagation algorithm in an artificial neural network was applied to grade the Burley type dried leaf tobacco. The success rate of grading in three-grade classification(1, 3, 5) was higher than the rate of grading in six-grade classification(1, 2, 3, 4, 5, off), on the average success rate of both the twenty-five local pixel-set and the sixteen local pixel-set. And, the average grading success rate using both shape and color features was higher than the rate using shape, color and texture features. Thus, the texture feature obtained by the spatial gray level dependence method was found not to be important in grading leaf tobacco. Grading according to the shape, color and texture features obtained by machine vision system seemed to be inadequate for replacing manual grading of Burely type dried leaf tobacco.

• Journal of Korea Multimedia Society
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• v.19 no.12
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• pp.1936-1942
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• 2016

This paper presents a mobile color-compensating application using a RGB color compensation algorithm. The proposed application enables color vision deficiencies to differentiate images which cannot be distinguished by them. The suggested mobile application has two functions: converting images taken by camera and converting contents in the device screen. The proposed application is computationally inexpensive, since it does not require color space transformation. Simulation results show that the proposed application enables color vision deficiencies to receive information expressed by colors such as subway line maps.

• 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.

• Journal of the Optical Society of Korea
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• v.17 no.4
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• pp.344-349
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• 2013

This paper proposes a simulation algorithm to assess the gradual yellowing vision of the elderly, which refers to the predominance of yellowness in their vision due to aging of the ocular optic media. This algorithm employed the spectral transmittance property of a yellow filter to represent the color appearance perceived by elderly people with yellow vision, and modeled the changes in the color space through a spectrum change in light using the yellow filter effect. The spectral reflectivity data of 1269 Munsell matte color chips were used as reference data. Under the standard conditions of a D65 illuminant and a $10^{\circ}$ observer of 1964 CIE, the spectrum of the 1269 Munsell colors were processed through the yellow filter effect to simulate yellow vision. Various degrees of yellow vision were modeled according to the transmittance percentage of the yellow filter. The color differences before and after the yellow filter effect were calculated using the DE2000 formula, and the color pairs were selected based on the color difference function. These color pairs are distinguishable through normal vision, but the color difference diminishes as the degree of yellow vision increases. Assuming 80% of yellow vision effect, 17 color pairs out of $(1269{\times}1268)/2$ pairs were selected, and for the 90% of yellow vision effect, only 3 color pairs were selected. The result of this study can be utilized for the diagnosis system of gradual yellow vision, making various types of test charts with selected color pairs.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.1
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• pp.44-49
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• 2003

This paper describes a method of estimating miniature train location by color vision for development of an intelligent railway system model. In the teal world, to control trains automatically, GPS(Global Positioning System) is indispensable to determine the location of trains. A color vision system was used for estimating the location of trains in an indoor experiment. Two different rectangular color bars were attached to the top of each train as a means of identifying them. Several trains were detected where they were located on the track by color feature, geometric features and moment invariant, and tracked simultaneously. In the experiment the identity, location and direction of each train were estimated and transferred to the control computer using serial communication. Processing speed of up to 8 frames/sec could be achieved, which was enough speed for the real-time train control.

• Journal of Biosystems Engineering
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• v.32 no.2 s.121
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• pp.130-135
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• 2007

An on-line real time grading and sorting system for dried oak mushrooms was developed for on-site application. Quality grades of the mushrooms were determined according to an industrial specification. Three dimensional visual quality features were used for the grading. A progressive color computer vision system with white LED illumination was implemented to develop an algorithm to extract external quality patterns of the dried oak mushrooms. Cap (top) and gil (stem) surface images were acquired sequentially and side image was obtained using mirror. Algorithms for extracting size, roundness, pattern and color of the cap, thickness, color of the gil and amount of rolled edge of the dried mushroom were developed. Utilizing those quality factors normal and abnormal ones were classified and normal mushrooms were further classified into 30 different grades. The sorting device was developed using microprocessor controlled electro-pneumatic system with stainless buckets. Grading accuracy was around 97% and processing time was 0.4 s in average.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.658-667
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• 1996

A computer vision system was developed to automatically detect and locate the oyster hinge line, one step in shucking an oyster. The computer vision system consisted of a personal computer, a color frame grabber, a color CCD video camera with a zoom lens, two video monitor, a specially designed fixture to hold the oyster, a lighting system to illuminate the oyster and the system software. The software consisted of a combination of commercially available programs and custom designed programs developed using the Microsoft CTM . Test results showed that the image resolution was the most important variable influencing hinge detection efficiency. Whether or not the trimmed -off-flat-white surface area was dry or wet, the oyster size relative to the image size selected , and the image processing methods used all influenced the hinge locating efficiency. The best computer software and hardware combination used successfully located 97% of the oyster hinge lines tested. This efficienc was achieve using camera field of view of 1.9 by 1.5cm , a 180 by 170 pixel image window, and a dry trimmed -off oyster hinge end surface.

• Journal of Biosystems Engineering
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• v.19 no.4
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• pp.380-396
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• 1994

A personal computer based color machine vision system with video camera and fluorescent lighting system was used to generate images of stationary tobacco leaves. Image processing algorithms were developed to extract both the geometric and the color features of tobacco leaves. Geometric features include area, perimeter, centroid, roundness and complex ratio. Color calibration scheme was developed to convert measured pixel values to the standard color unit using both statistics and artificial neural network algorithm. Improved back propagation algorithm showed less sum of square errors than multiple linear regression. Color features provide not only quality evaluation quantities but the accurate color measurement. Those quality features would be useful in grading tobacco automatically. This system would also be useful in measuring visual features of other agricultural products.