• International Journal of Internet, Broadcasting and Communication
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• v.7 no.2
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• pp.1-8
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• 2015

Tracking of an object in 3D space performed in real-time is a significant task in different domains from autonomous robots to smart vehicles. In traditional methods, specific data acquisition equipments such as radars, lasers etc, are used. Contemporary computer technology development accelerates image processing, and it results in three-dimensional stereo vision to be used for localizing and object tracking in space. This paper describes a system for tracking three dimensional motion of an object using color information in real time. We create stereo images using pair of a simple web camera, raw data of an object positions are collected under realistic noisy conditions. The system has been tested using OpenCV and Matlab and the results of the experiments are presented here.

• Journal of Industrial Technology
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• v.28 no.B
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• pp.143-148
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• 2008

A real-time face detection is to find human faces robustly under the cluttered background free from the effect of occlusion by other objects or various lightening conditions. We propose a face detection system for real-time applications using wavelet decomposition method based on Gabor features. Firstly, skin candidate regions are extracted from the given image by skin color filtering and projection method. Then Gabor-feature based template matching is performed to choose face cadidate from the skin candidate regions. The chosen face candidate region is transformed into 2-level wavelet decomposition images, from which feature vectors are extracted for classification. Based on the extracted feature vectors, the face candidate region is finally classified into either face or nonface class by the Levenberg-Marguardt back-propagation neural network.

• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.745-748
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• 2008

The theory of Bartleson and Breneman that the perceived image contrast changes with surround luminance (the lighter surround provides higher contrast) was tested an over bright condition($8500d/m^2$). Contrarily to the Bartleson and Breneman's results, we observed the fact that perceived constrast was decreased when surround huminance increased from dark to over bright through two sets of psychophysical experiments based upon both uniform gray patches and complex color images.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.05a
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• pp.322-326
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• 2006

본 논문에서는 내시경 영상에 대해 위암 영역을 자동으로 추출하는 방법을 제안한다. 본 논문에서는 내시경 영상을 획득하는 과정에서 발생하는 조명에 의한 잡음과 굴곡에 의해 발생하는 그림자에 의한 잡음 부분을 해결하기 위해서 HSI의 채도와 밝기 값을 이용하여 잡음 영역을 제거한다. 그리고 헤모글로빈 색소 정보를 나타내는 IHb값을 이용하여 전자 내시경 영상에서 유사한 헤모글로빈 색소 정보를 가지는 영역으로 분할한다. 분할된 영역들 중에서 RGB의 각 채널과 헤모글로빈 색소가 높게 나타나면 후보 영역으로 설정한다. 설정된 후보 영역 중에서 위암 영역의 형태학적인 특징 정보를 이용하여 위암 영역을 추출한다. 실제 전문의가 제공한 20개의 내시경 영상을 대상으로 실험한 결과, 제안된 위암 추출 방법으로 17개가 정확히 추출되었고 3개의 내시경 영상에서는 위암 영역이 정확히 추출되지 않았다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.292-296
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• 2004

본 논문에서는 컬러영상에서 Pulse-Coupled Neural Network를 이용한 얼굴 추출 알고리즘의 성능을 향상시키는 방법에 대하여 논의하였다. 색상정보를 이용한 얼굴 추출 알고리즘은 얼굴의 기울어진 정도나 크기 둥에 영향을 받지 않으므로, 형태정보를 이용한 얼굴 추출 알고리즘에 비해 비교우위를 가진다. 그러나 조명의 변화가 심하거나, 피부색과 유사한 배경이 포함되어 있을 경우 적절한 성능을 내기 어렵다. 이러한 문제점들을 해결하기 위해 본 연구에서는 넓은 피부색 영역을 추출하고, Pulse-Coupled Neural Network를 통해 공간적으로 근접한 피부색 동종영역을 분리해 내는 방법을 사용하였다. 그리고 피부색 영역에 해당하는 픽셀들이 다른 영역들에 비해 큰 값을 갖도록 하여, Pulse-Coupled Neural Network의 linking coefficient를 보다 쉽게 결정하도록 하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.175-178
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• 2010

Slow movement of snail can be a benefit since it means less speed of tracking is required to get accurate movement track, but in the other side it is difficult to extract the object because the snail is almost as static as the background. In this paper, we present a technique to track the snail by using one of its common characteristic, dark color of its shell. The technique needs to be robust to illumination change since the experiment is usually to observe the movement of snail both at bright and dim condition. Snail position coordinate in 3D space is calculated using orthogonal stereo vision which combines the information from two images taken from cameras at the top and in front of the aquarium. Experimental results show this technique does not need prior background image extraction and robust to gradual or sudden illumination change.

• 한국정보디스플레이학회:학술대회논문집
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• 2006.08a
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• pp.1255-1258
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• 2006

PM OLED has the line-disturbance when eyes can detect the driving line status in the shaking situation. It is closely related with the lighting intensity and the lighting time during the line driving. .In this paper we suggest the frame part method for eliminating lineflash appearance. Frame part is a driving method of PM OLED, which divides one frame into several inner-frame parts to reduce the color interference between closely related pixels and to lessen the lineflash appearance which disturbs viewer to perceive the images. Frame part groups one frame into several inner-frame parts and have inner-frame rate higher than the frame rate. Frame part could be used in most of applications in PM OLED systems to enhance the total performance of screen quality.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.119-122
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• 2001

This paper discusses the peg-in-hole task of chamferless parts using force/moment/vision sensors. The directional error occurring during the task are categorized into two cases according to the degree of initial errors, And different Mechanical analysis has been accomplished for each cases. This paper proposes an algorithm which enables to reduce intial directional error using digital Images acquired from hand-eyed vision sensor, And to continue the task even with the large directional error by adjusting the error using digital image processing. The effectiveness of the algorithm has been demonstrated through experimentation using 5-axis robot equipped with a developed controller force/moment sensor and color digital camera on its hand.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.34-36
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• 2009

This paper proposes an effective lane detection algorithm using hugh transform and lane model. The proposed lane detection algorithm includes two major components, i.e., lane marks segmentation and an exact lane extraction using a novel postprocessing technique. The first step is to segment lane marks from background images using HSV color model. Then, a novel postprocessing is used to detect an exact lane using Hugh transform and lane models(linear and curved lane models). The postprocessing consists of three parts, i.e, thinning process, Hugh Transform and filtering process. We divide input image into three regions of interests(ROIs). Based on lane curve function(LCF), we can detect an exact lane from various extracted lane lines. The lane models(linear and curved lane mode]) are used in order to judge whether each lane segment is fit or not in each ROIs. Experimental results show that the proposed scheme is very effective in lane detection.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.853-854
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• 2008

The terrain perception technology using passive sensors plays a key role to enhance autonomous mobility for UGV. We present an effective method to classify terrain covers based on the color information. Considering a real-time implementation, neural network is applied for the terrain classifier and wavelet features extracted from the images are used. Test results show that the proposed algorithm has a promising classification performance.