• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2005.07a
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• pp.72-73
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• 2005

In this paper, the simulation of the n-p-n-p layer stacked color detector is presented. A color detector based on vertically integrated structures of silicon can overcome color moire or color aliasing effect. The color detector is designed to separate the fundamental chromatic components at each junction and exhibits maxima of the spectral sensitivity at red, green, and blue region, respectively. From this result, it is observed that the spectral response can be controlled by the doping concentration and structure of the devices.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.15 no.7
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• pp.583-590
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• 2002

In this paper, a new Silicon on Insulator (SOI)-based photodetector was proposed, and its basic operation principle was explained. Fabrication steps of the detector are compatible with those of conventional SOI CMOS technology. With the proposed structure, RGB (Read, Green, Blue) which are three primary colors of light can be realized without using any organic color filters. It was shown that the characteristics of the SOI-based detector are better than those of bulk-based detector. To see the response characteristics to the green (G) among RGB, SOI and bulk NMOSFETS were fabricated using $1.5\mu m$ CMOS technology and characterized. We obtained optimum optical response characteristics at $V_{GS}=0.35 V$ in NMOSFET with threshold voltage of 0.72 V. Drain bias should be less than about 1.5 V to avoid any problem from floating body effect, since the body of the SOI NMOSFET was floated. The SOI and the bulk NMOSFETS shown maximum drain currents at the wavelengths of incident light around 550 nm and 750 nm, respectively. Therefore the SOI detector is more suitable for the G color detector.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1093-1096
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• 1999

In this paper, video image segmentation algorithm based on color histogram and change detector is proposed. Color histograms are calculated from both changed region which is detected in the previous and current frame and unchanged region. With each histogram, modes and valleys are detected. Then, color vectors are calculated by averaging pixels in modes. Markers are extracted by labeling color vectors that represent modes, the watershed algorithm is applied to determine uncertain region. In growing region, the root mean square(RMS) of the distance between average pixel in marker region and adjacent pixel is used as a measure. The proposed algorithm based on color histogram and change detector segments video image fastly and effectively. And simulation results show that the proposed method determines the exact boundary between background and foreground.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.7
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• pp.1566-1573
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• 1997

In this paper, we propose a favorite color correction algorithm for color enhancement in color application system which represent preferred colors for viewer's demands. The proposed algorithm corrects skin color which is widely used as a reference color for color control of color application system, blue color which is directly related to tri-stimulus values, and green color which has higher visual sensitivity. In the proposed algorithm, the vaiation range of phase detector output voltage was minimized for the favorite color saturation changes, thus the favorite from the burst signal for the phase detector characteristic, thus the favorite color was easilty detected from the other color without overlapping of correctionranges.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.353-362
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• 1993

The purpose of this study is to develop a crop-row detector which can be applied to an automatic row following control for cultivators or thinning machines. In this report, a possibility of new crop-row detecting method was discussed. This detecting method consists of two principal means. One is the hardware means to convert the two dimensional crop-row vision to the compacted one dimensional information. The conversion is achieved by a color line sensor and a rotating mirror. In order to extract crop-row , R and G signals of RGB color system are used. The locations of two different points on the target row are detected by this means. Another is the software means to estimate the offset value and the heading angle between the detector and the target row which can be assumed as a straight line. As a result of discussion, it was concluded that this detecting method would be accurate enough for practical use.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.3
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• pp.241-246
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• 2016

Nowadays many people have an interest in facial expression and the behavior of people. These are human-robot interaction (HRI) researchers utilize digital image processing, pattern recognition and machine learning for their studies. Facial feature point detector algorithms are very important for face recognition, gaze tracking, expression, and emotion recognition. In this paper, a cascade facial feature point detector is used for finding facial feature points such as the eyes, nose and mouth. However, the detector has difficulty extracting the feature points from several images, because images have different conditions such as size, color, brightness, etc. Therefore, in this paper, we propose an algorithm using a modified cascade facial feature point detector using a convolutional neural network. The structure of the convolution neural network is based on LeNet-5 of Yann LeCun. For input data of the convolutional neural network, outputs from a cascade facial feature point detector that have color and gray images were used. The images were resized to $32{\times}32$. In addition, the gray images were made into the YUV format. The gray and color images are the basis for the convolution neural network. Then, we classified about 1,200 testing images that show subjects. This research found that the proposed method is more accurate than a cascade facial feature point detector, because the algorithm provides modified results from the cascade facial feature point detector.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.2
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• pp.375-382
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• 2010

In this paper, we propose the simplified and improved system of One Color Detector to protect color distortion of simple color images in the processed of Auto White Balance (AWB). The proposed One Color Detector is based on Grayworld algorithm which controls color compensation except one color in simple image and widely applies for mobile phone camera because of high efficiency. This system can be suitable for diverse image size, and let user control the threshold in diverse size and environments compared with conventional system. Also the hardware size of the proposed system is reduced by 80% over that of the conventional one.

• Journal of KIISE:Software and Applications
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• v.36 no.7
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• pp.548-559
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• 2009

The cascade face detector learned by Adaboost algorithm, which was proposed by Viola and Jones, is state of the art face detector due to its great speed and accuracy. In spite of its great performance, it still suffers from false alarms, and more computation is required to reduce them. In this paper, we want to reduce false alarms with less computation using facial color. Using facial color information, proposed face detection model scans sub-window efficiently and adapts a fast face/non-face classifier at the first stage of cascade face detector. This makes face detection faster and reduces false alarms. For facial color filtering, we define a facial color membership function, and facial color filtering image is obtained using that. An integral image is calculated from facial color filtering image. Using this integral image, its density of subwindow could be obtained very fast. The proposed scanning method skips over sub-windows that do not contain possible faces based on this density. And the face/non-face classifier at the first stage of cascade detector rejects a non-face quickly. By experiment, we show that the proposed face detection model reduces false alarms and is faster than the original cascade face detector.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.239-245
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• 2004

A hue-based noise-tolerant corner detector is proposed for the exact detection of the real corners in spite of the shadows and random noise. Based on the fact that the hue gradient at the border of the opaque objects' shadow is smaller than the intensity gradient in HSI (hue-saturation-intensity) color space, the effects of shadow are eliminated by introducing the hue-weighted combination of vector gradient to the proposed corner detector. Furthermore, the proposed corner detector is robust to random noise by offsetting the contribution to the corner candidate when the polarities of the color gradients of the pixel pairs are out of phase each other. Results of the experiment show that the proposed corner detector can effectively detect the real corners.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1956-1960
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• 1991

This paper describes the measured results upon monochromatic light, compound light, and light emanated from light emitting diodes by a simplified wavemeter with a semiconductor color sensor. Since a single unit element of a semiconductor color sensor with two PN junction photodiodes has been developed, the author has fabricated the simplified wave detector by using the element. The simplified wive detector has been measured results upon monochromatic light, compound light, and light emanated from light emitting diodes. Since luminescent color of each diode locates in luminosity region, comparison of measured values of PD-150 and PD-151 resulted no remarkable difference in averaged wave length. As for monochromatic light, PD-151 showed very cross value to the color filter peak value rather than PD-150. As for compound light, PD-150 has shown such influence of long wave length light which reaches to near infrared ray with respect to PD-151.