• The KIPS Transactions:PartB
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• v.17B no.3
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• pp.207-214
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• 2010

A method of the region extraction and recognition of a traffic light and speed sign board in the real road environment is proposed. Traffic light was recognized by using brightness and color information based on HSI color model. Speed sign board was extracted by measuring red intensity from the HSI color information We improve the recognition rate by performing an incline compensation of the speed sign for directions clockwise and counterclockwise. The proposed algorithm shows a robust recognition rate in the image sequence which includes traffic light and speed sign board.

• Journal of Broadcast Engineering
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• v.24 no.2
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• pp.353-356
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• 2019

The main functionality of occupancy sensors is to determine the existence of humans in the space. If the space is occupied, a light is on and for vacancy, the light automatically turns off. In this letter, the functionality is realized by the utilization of color information. The color information of incoming people is saved. For outgoing people, their color distribution is compared with the saved information, thus providing the recognition of the outgoing people. For the comparison, four similarity metrics are examined to validate the proposed method.

• The KIPS Transactions:PartB
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• v.11B no.3
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• pp.317-326
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• 2004

This paper presents a new method for the detection of multiple pedestrians and tracking of a specific pedestrian using color information from a moving camera. We first extract motion vector on the input image using BMA. Next, a difference image is calculated on the basis of the motion vector. The difference image is converted to a binary image. The binary image has an unnecessary noise. So, it is removed by means of the proposed noise deletion method. Then, we detect pedestrians through the projection algorithm. But, if pedestrians are very adjacent to each other, we separate them using RGB color information. And we track a specific pedestrian using RGB color information in center region of it. The experimental results on our test sequences demonstrated the high efficiency of our approach as it had shown detection success ratio of 97％ and detection failure ratio of 3％ and excellent tracking.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.11a
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• pp.140-141
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• 2016

기존의 사람 계수 측정 시스템은 적외선 빔이나 열 감지 영상 장치를 통해 측정하였다. 하지만 이와 같은 방법으로 측정하면 객체가 들어가거나 나가는 정보는 제공하지 않는다. 이에 본 논문은 고정된 카메라를 이용하여 각 사람의 피부색과 옷차림 등의 RGB 정보를 이용한 사람 계수 측정 기법을 제안한다. RGB카메라 영상을 통하여 객체의 RGB 히스토그램을 얻은 후 각 객체에 대해 Bhattacharyya metric을 통한 histogram similarity을 계산하여 객체 추적 및 분류를 통해 사람 계수 측정을 한다. 제안된 시스템은 C/C++을 기반으로 구현하여, 사람 계수 측정 성능을 평가하였다.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.159-167
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• 2013

In stereo-view system, variations of target camera position or lighting conditions cause discrepancies on the luminance and chrominance components of stereo views. These discrepancies lead to inaccurate frame view prediction and low quality of 3 D video coding. In this paper, an efficient histogram interval calibration method is proposed for stereo-view coding, so as to compensate for the luminance component of target view. First the proposed method is analyzed by the histogram of the target image frame. Then, it divide two sections of histogram of that frame to correct the color discrepancies. Secondly, each section of the target frame is corrected the luminance component by identify the maximum matching region between the reference frame and the target frame. We have verified our proposed histogram matching method in comparison with the other color correction ones. Experimental results show that it can correct better luminance calibration results of PSNR(Peak Signal to Noise Ratio) and has less computation time.

• Journal of Korea Multimedia Society
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• v.16 no.8
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• pp.927-933
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• 2013

Face detection algorithm of OpenCV recognizes the faces by Haar matching between input image and Haar features which are learned through a set of training images consisting of many front faces. Therefore the face detection method by Haar matching yields a high face detection rate for the front faces but not in the case of the pan and deformed faces. On the assumption that distributional characteristics of color histogram is similar even if deformed or side faces, a face detection method using the histogram pattern matching is proposed in this paper. In the case of the missed detection and false detection caused by Haar matching, the proposed face detection algorithm applies the histogram pattern matching with the correct detected face area of the previous frame so that the face region with the most similar histogram distribution is determined. The experiment for evaluating the face detection performance reveals that the face detection rate was enhanced about 8% than the conventional method.

• Journal of Information Technology Application
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• v.3 no.2
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• pp.133-147
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• 2001

This paper proposed a new algorithm for binarization and removal of noises in color images with characters and pictures. Binarization was performed by threshold which had computed with color-relationship relative to the number of pixel in background and character candidates and pre-threshold for dividing of background and character candidates in input images. The pre-threshold has been computed by the histogram of R, G, B In respect of the images, while background and character candidates of input images are divided by the above pre-threshold. As it is possible that threshold can be dynamically decided by the quantity of the noises, and the character images are maintained and the noises are removed to the maximum. And, in this study, we made the noise pattern table as a result of analysis in noise pattern included in the various color images aiming at removal of the noises from the Images. Noises included in the images can figure out Distribution by way of the noise pattern table and pattern matching itself. And then this Distribution classified difficulty of noises included in the images into the three categories. As removal of noises in the images is processed through different procedure according to the its classified difficulties, time required for process was reduced and efficiency of noise removal was improved. As a result of recognition experiments in respect of extracted characters in color images by way of the proposed algorithm, we conformed that the proposed algorithm is useful in a sense that it obtained the recognition rate in general documents without colors and pictures to the same level.

• Journal of the Korea Computer Graphics Society
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• v.18 no.2
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• pp.9-15
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• 2012

In this paper, we propose a method to segment a color image into several meaningful regions. We suppose that the meaningful region has a set of colors with high frequency in the color image. To find these colors, the color image is represented as several sets of color points in RGB space. And when we use the density of points defined in this method, color belonging to a dense region of color points in RGB space refers to the color that appeared frequently in the image. Eventually, we can find meaningful regions by looking for regions with high density of color points using our level set function in RGB space. However, if a meaningful region does not have a contiguous region of the sufficient size in the image, this is not a meaningful region but meaningless region. Thus, the pixels in the meaningless region are assigned to the biggest meaningful region belonging to its neighboring pixels in the color image. Our method divides the color image into meaningful regions by applying the density of color points to level set function in RGB space. This is different from the existing level set method that is defined only in 2D image.

• Journal of KIISE:Databases
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• v.37 no.5
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• pp.267-274
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• 2010

Recently, color harmony that decides the value of design is becoming important. In the paper, we propose a method that allows us to easily use harmonious colors in computer systems. Since existing work has focused on finding new color harmony rules or rules that translate emotional words into colors, a method that models these rules in the computer system has not been discussed in depth. In this paper, we model a color system and color harmony rules as a relational database and queries on this database, respectively.

• Korean Journal of Optics and Photonics
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• v.30 no.3
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• pp.101-105
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• 2019

An LCD backlight unit (BLU) using RGB light sources is designed and simulated, in order to improve its optical energy efficiency. A color-matching BLU is designed with a lenticular lens array (LLA) with elements that image the linear RGB light sources onto the RGB subpixels of the color filter. Type-A and Type-B simulations are performed, according to the location of the light sources. As a result, the luminance increases to 210% in Type-A and 270% in Type-B respectively. The optimum values for the height and the gap of the LLA for maximum efficiency are found to be $25{\mu}m$ and $3{\mu}m$ respectively.