• Journal of Institute of Control, Robotics and Systems
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• v.21 no.12
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• pp.1122-1129
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• 2015

This paper suggests a method of detecting traffic lights for vehicles by combining the HSV(hue saturation value) color model, morphometric characteristics, and location information appearing on consecutive images in daytime. In order to detect the traffic light, the color corresponding to the signal lights should be explored. It is difficult to detect traffic lights among colors of lights from buildings, taillight of cars, leaves, placards, etc. The proposed algorithm searches for the traffic lights from many candidates using morphometric characteristics and location information in consecutive images. The recognition process is divided into three steps. The first step is to detect candidates after converting RGB channel into HSV color model. The second step is to extract the boundaries between the housing of traffic lights and background by exploiting the assumption that the housing has lower brightness than the surrounding background. The last step is to recognize the signal light after eliminating the false candidates using morphometric characteristics and location information appearing on consecutive images. This paper demonstrates successful detection results of traffic lights from various images captured on the city roads.

• Ceramist
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• v.21 no.1
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• pp.55-63
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• 2018

Recently, display technology has been focused in regard with with color reproduction, contrast ratio, image resolution and color bit. Among these technologies, the color reproducibliity of White, Red, Green, and Blue is associated with the TV plaform and is expressed as a major technology. Major TV platforms are divided into three categories since 2015, including LCD-based phosphor coverted LED BLU technology, QD sheet technology using nano-sized quantum dots, and OLED technology. In this paper, we describe the color reproducibility definition and background, luminescent materials with wide color gamut, color reproducibility of TV display performance, and discuss about next luminescent materials.

• Journal of Korea Multimedia Society
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• v.11 no.11
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• pp.1515-1524
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• 2008

This paper proposes a method that detects a license plate in complex background using a multiple-color model and character layout information. A layout of a green license plate is different from that of a white license plate. So, this study used a strategy that firstly assumes the plate color and then utilizes its layout information. At first, it extracts green areas from an input image using a multiple-color model which combined HIS and YIQ color models with RGB color model. If green areas are detected, it searches the character layout of the green plate by analyzing the connected components in each areas. If not detected, it searches the character layout of the white plate in all area. Finally, it extracts a license plate by grouping the connected components which corresponds to characters. Experimental result shows that 98.1% of 419 input images are correctly detected. It also shows that the proposed method is robust against illumination, shadow, and weather condition.

• The Journal of the Korea Contents Association
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• v.11 no.5
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• pp.125-137
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• 2011

Recently the research on the system using images taken from camera phones as input is actively conducted. This paper proposed a system that shows wine pictures which are similar to the input wine label in order. For the calculation of the similarity of images, the representative color of each cell of the image, the recognized text color, background color and distribution of feature points are used as the features. In order to calculate the difference of the colors, RGB is converted into CIE-Lab and the feature points are extracted by using Harris Corner Detection Algorithm. The weights of representative color of each cell of image, text color and background color are applied. The image similarity is calculated by normalizing the difference of color similarity and distribution of feature points. After calculating the similarity between the input image and the images in the database, the images in Database are shown in the descent order of the similarity so that the effort of users to search for similar wine labels again from the searched result is reduced.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.12
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• pp.2355-2373
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• 2011

Vision-based vehicle detector systems are becoming increasingly important in ITS applications. Real-time operation, robustness, precision, accurate estimation of traffic parameters, and ease of setup are important features to be considered in developing such systems. Further, accurate vehicle detection is difficult in varied complex traffic environments. These environments include changes in weather as well as challenging traffic conditions, such as shadow effects and jams. To meet real-time requirements, the proposed system first applies a color background to extract moving objects, which are then tracked by considering their relative distances and directions. To achieve robustness and precision, the color background is regularly updated by the proposed algorithm to overcome luminance variations. This paper also proposes a scheme of feedback compensation to resolve background convergence errors, which occur when vehicles temporarily park on the roadside while the background image is being converged. Next, vehicle occlusion is resolved using the proposed prior split approach and through reasoning for rule-based tracking. This approach can automatically detect straight lanes. Following this step, trajectories are applied to derive traffic parameters; finally, to facilitate easy setup, we propose a means to automate the setting of the system parameters. Experimental results show that the system can operate well under various complex traffic conditions in real time.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.2
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• pp.112-119
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• 2009

This paper describes a robust visual surveillance algorithm under outdoor environment. One of the difficult problems for outdoor is to obtain effective updating process of background images. Because background images generally contain the shadows of buildings, trees, moving clouds and other objects, they are changed by lapse of time and variation of illumination. They provide the lowering of performance for surveillance system under outdoor. In this paper, a robust algorithm for visual surveillance system under outdoor is proposed, which apply the mixture Gaussian filter and color invariant property on pixel level to update background images. In results, it was showed that the moving objects can be detected on various shadows under outdoor.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.139-142
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• 2001

This paper presents a highly fast and accurate facial region extraction method by using the skin-color-reference map and motion information. First, we construct the robust skin-color-reference map and eliminate the background in image by this map. Additionally, we use the motion information for accurate and fast detection of facial region in image sequences. Then we further apply region growing in the remaining areas with the aid of proposed criteria. The simulation results show the improvement in execution time and accurate detection.

• 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.

• Korean Journal of Human Ecology
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• v.3 no.1
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• pp.71-80
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• 1994

The purpose of this study was to investigate the relationship between color preference and personality traits & personal factor among secondary school girls. Personality traits were measured. with Lee et al's Personality Scale. The questioniare measuring color preference consists of items designed to assess color and clothing color(T-shirt and slacks) preference and color repugnance. These questionaire were administerd to 576 middle and high school girls in Chungbuk Province. As statistical analysis, chi-square, F-test and correlation were used. The result were; 1. The order of prefered colors were white, yellow and green, and the order of repugnated colors were gray, red and red purple. 2. Personality traits was no signifcant related to color perference and repugnance. 3. Color perference was positively related to age, residential area and type of school. Color repugnance was positively related to age, residential area, type of school and educational background of mother. 4. Yellow red, yellow and white T-shirt were prefered in spring and autumn, white and blue T-shirt were prefered in summer, and black, gray and red T-shirt were prefered in winter. White and blue slacks were prefered in spring, summer and autumn seasons, and black, gray and blue slacks were prefered in winter. 5. There was a positive relationship between color perference and T-shirt color, but was no positive relationship between color perference and slacks color.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.6 s.312
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• pp.85-96
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• 2006

This paper deal with a method for efficient placing 2 dimensional virtual labels on the view plane. The proposed method has suitable computational costs for realtime processing and it overcomes the local minima problem which is not solved in previous automatic label placement algorithms, and also it enhances readability by placing labels in less congestion area on the view plane. Background analysis must be considered for label placement. However previous works do not concern with this problem seriously. And furthermore, automatic label placement algorithm and background analysis algorithm have been studied separately in their own field. This paper proposed the background analysis method using background color and texture component to enhance readability, and it is the first research about analyzing the background of color image and applying it in automatic label placement field. This paper shown improved placement performance through combining automatic label placement algorithm and background analysis algorithm organically, and various experiments verified it.