• Science of Emotion and Sensibility
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• v.16 no.4
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• pp.557-566
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• 2013

This study is to investigate the color emotion associations of the color vision defectives, considering that the colors do have an effect on human emotional conditions. To realize this investigation, firstly we selected 100 normal persons (group C)and other 34 color vision defectives(group A), dividing the last group into two small groups as protanomaly group(group P) with 8 persons and deuteranomaly group(group D) with 16 persons. All participants have been offered to select one color from ten colors for each of three positive emotions such as 'favorite', 'happy' and 'friendly' and of three negative emotions like 'sad', 'disliked' and 'awkward'. And they selected another one color for each active and passive emotions. For 'favorite color' the group C selected 'blue' and 'red' while the group A chose 'blue'. For 'happy color' the two groups selected 'yellow'. For 'friendly color' the group C chose 'green', but the group A selected 'blue'. For 'sad color' the group C preferred 'blue', but the group A chose 'purple'. For 'disliked color' all groups selected 'bluish green'. For 'awkward color' the two groups preferred 'bluish green'. For 'active color' all groups selected 'red'. And for 'passive color' the group C chose 'bluish green', but the group A selected 'blue'. Depending on the type of color vision deficiency(group P and group D) some more differences were revealed relatively. These results should be applied to develop some intelligent color conversion technology for enhancing the usability of culture contents for color vision defectives.

• 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.22 no.2
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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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• v.32 no.4
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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.

• Journal of Sensor Science and Technology
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• v.21 no.1
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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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• v.6 no.6
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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.

• Journal of Korean Ophthalmic Optics Society
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• v.1 no.1
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• pp.127-138
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• 1996

• ETRI Journal
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• v.33 no.1
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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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• 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 Digital Contents Society
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• v.15 no.6
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• pp.751-761
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• 2014

Color deficient people do not have sufficient discernment for the colors with low saturation and brightness and at the same time express their negative emotions regarding emotion distortion. The purpose of recovering the distortion of the vision which is the basis for emotion is to increase positive emotions rather than negative ones that those with color vision deficiency feel when they experience digital culture contents. Contrast increases saturation and brightness by differing the direction of their conversion and by doing so, delivers emotion distortion such as dynamic vs. static and vivid vs. somber that the original images intend to convey to those with color vision deficiency by reducing such a contrast. In this respect, this study proposes a contrast-based color conversion method to convert saturation and brightness in the zone of color conversion and identifies if this method can reduce emotion distortion by using color conversion simulation and user test.