• 감성과학
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• 제16권4호
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• pp.557-566
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• 2013

본 연구는 색각이상자들의 색채 감성 연상의 실태 조사 목적에서 기획되었다. 정상인 100명과 색각이상자 34명으로 피실험 집단을 구성하였고, 색각이상자를 '적색약' 집단 8명과 '녹색약' 16명으로 세분하여, 좋아하는 색, 행복한 색, 친근한 색, 싫어하는 색, 슬픈 색, 거북한 색, 적극적인 색과 소극적인 색 등 항목에 대해서 먼셀이 제안한 기본 10색 가운데 하나씩만 선택하도록 하였다. 정상인 집단의 좋아하는 색은 파랑과 빨강이고, 행복한 색은 노랑이며, 친근한 색은 초록이었다. 색각이상자 집단은 좋아하는 색으로 파랑을, 행복한 색으로 노랑을, 친근한 색으로 파랑을 선택하였다. 또한 정상인 집단이 싫어하는 색을 청록으로, 슬픈 색으로 파랑을, 거북한 색으로 청록을 선택한 것과 비교하여, 색각이상자 집단은 싫어하는 색으로 청록을, 슬픈 색으로 자주를, 거북한 색으로 청록을 선택하였다. 정상인 집단이 적극적인 색과 소극적인 색으로 빨강과 청록을 선택한 반면, 색각이상자 집단은 각각 빨강과 파랑을 선택하였다. 이는 색각이상자들의 일상생활에 있어서 색채의 왜곡된 수용이 감성왜곡으로 연결되어 일상생활에서의 부정적 요소가 되지 않도록 유도하는 색 구성 작업에 활용되고, 특히 문화콘텐츠 이용 편의성 등에 활용될 수 있을 것이다.

• 제어로봇시스템학회논문지
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• 제9권1호
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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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• 제22권2호
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• pp.210-216
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• 1997

A study to select ground colors of Fuji apple for maturity index which are needed to standardize grading of the apples is presented. Two extreme colors of immature and fully mature Fuji and Zonagold apples produced in Korea were determined. Various ground colors of Fuji apple between the two extreme colors were collected and classified by human vision and colors of Fuji apple for maturity index were selected from the classification. Coordinates of the selected colors in xy chromaticity diagram were determined by spectrophotometers to define them in a standard coordinate system. Coordinates of the colors in r-g chromaticity diagram using a color machine vision system were also determined to use the colors in apple grading by the machine vision system. Grading Fuji apples using the machine vision system was performed and result of the grading was compared with Ending results of human vision and colorimeter. The comparison was performed with the same Fuji apple samples and showed 65% md 75% of same grades, respectively, as the grades determined by the machine vision system. Differences of fading performance between the compared three grading methods were explained as mainly because of the differences of observation area of the grading methods.

• Journal of Biosystems Engineering
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• 제32권4호
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• pp.256-262
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• 2007

Image processing systems have been used to measure the plant parameters such as size, shape and structure of plants. There are yet some limited applications for evaluating plant colors due to illumination conditions. This study was focused to present adaptive methods to analyze plant leaf color regardless of illumination conditions. Color patches attached on the calibration bars were selected to represent leaf colors of lettuces and to test a possibility of health monitoring of lettuces. Repeatability of assigning leaf colors to color patches was investigated by two-tailed t-test for paired comparison. It resulted that there were no differences of assignment histogram between two images of one lettuce that were acquired at different light conditions. It supported that use of the calibration bars proposed for leaf color analysis provided color constancy, which was one of the most important issues in a video color analysis. A health discrimination equation was developed to classify lettuces into one of two classes, SOUND group and POOR group, using the machine vision. The classification accuracy of the developed health discrimination equation was 80.8%, compared to farmers' decision. This study could provide a feasible method to develop a standard color chart for evaluating leaf colors of plants and plant health monitoring system using the machine vision.

• 센서학회지
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• 제21권1호
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• pp.28-33
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• 2012

The visual sensing of human hands plays an important part in many man-machine interaction/interface systems. Most existing visionbased hand detection techniques depend on the color cues of human skin. The RGB color image from a vision sensor is often transformed to another color space as a preprocessing of hand detection because the color space transformation is assumed to increase the detection accuracy. However, the actual effect of color space transformation has not been well investigated in literature. This paper discusses a comparative evaluation of the pixel classification performance of hand skin detection in four widely used color spaces; RGB, YIQ, HSV, and normalized rgb. The experimental results indicate that using the normalized red-green color values is the most reliable under different backgrounds, lighting conditions, individuals, and hand postures. The nonlinear classification of pixel colors by the use of a multilayer neural network is also proposed to improve the detection accuracy.

• Current Optics and Photonics
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• 제6권6호
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• pp.608-618
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• 2022

By analyzing the signal-to-noise ratio (SNR) theory of the conventional true color night vision system, we found that the output image SNR is limited by the wavelength range of the system response λ₁ and λ₂. Therefore, we built a double-channel four-band true color night vision system to expand the system response to improve the output image SNR. In the meantime, we proposed an image fusion method based on principal component analysis (PCA) and nonsubsampled shearlet transform (NSST) to obtain the true color night vision images. Through experiments, a method based on edge extraction of the targets and spatial dimension decorrelation was proposed to calculate the SNR of the obtained images and we calculated the correlation coefficient (CC) between the edge graphs of obtained and reference images. The results showed that the SNR of the images of four scenes obtained by our system were 125.0%, 145.8%, 86.0% and 51.8% higher, respectively, than that of the conventional tri-band system and CC was also higher, which demonstrated that our system can get true color images with better quality.

• 한국안광학회지
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• 제1권1호
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• pp.127-138
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• 1996

• ETRI Journal
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• 제33권1호
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• pp.71-77
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• 2011

Up to 10% of the global population suffers from color vision deficiency (CVD) [1], especially deuteranomaly and protanomaly, the conditions in which it is difficult to discriminate between red and green hues. For those who suffer from CVD, their career fields are restricted, and their childhood education is frustrating. There are many optical eye glasses on the market to compensate for this disability. However, although they are attractive due to their light weight, wearing these glasses will decrease visual brightness and cause problems at night. Therefore, this paper presents a supplementary device that comprises a head-mounted display and an image sensor. With the aid of the image processing technique of digital color space adjustment implemented in a high-speed field-programmable gate array device, the users can enjoy enhanced vision through the display without any decrease in brightness.

• Journal of Biosystems Engineering
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• 제22권1호
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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.

• 디지털콘텐츠학회 논문지
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• 제15권6호
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• pp.751-761
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• 2014

색각 이상자들은 채도와 명도가 낮은 색채들에 대해 분별력을 갖지 못할 뿐 아니라 감성 왜곡과 관련하여 부정적인 감성을 표출한다. 감성의 기본이 되는 감각에 대한 왜곡을 바로 잡고자 함은 색각이상자들이 디지털 문화콘텐츠에 접할 때 느끼는 부정적인 감성보다 긍정적인 감성을 높이기 위해서이다. 대비는 채도와 명도간의 변환되는 방향이 다르게 하여 높이고, 이를 통해 원본 이미지가 전달하는 동적과 정적, 선명함과 칙칙함이라는 감각 왜곡을 감소시켜 색각 이상자에게 전달한다. 이를 색변환이 이뤄지는 영역에 대하여 채도와 명도를 변환하는 대비기반 색변환 방법을 제안하고 이 방법이 감각 왜곡을 감소시킨다는 것을 색변환 시뮬레이션과 사용자 테스트를 사용하여 확인한다.