• Journal of Digital Convergence
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• v.13 no.9
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• pp.183-189
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• 2015

In this paper, we propose an object tracking method using the color information of the image in surveillance network. This method perform a object detection using of adaptive color model. Object contour detection plays an important role in application such as object recognition. Experimental results demonstrate successful object detection over a wide range of object's variation in color and scale. In applications to detect an object in real time, when transmitting a large amount of image data it is possible to find the mode of a color distribution. The specific color of an object is modified at dynamically changing color in image. So, this algorithm detects the tracking area information of object within relevant tracking area and only tracking the movement of that object.Through experiments, we show that proposed method is more robust than other methods under certain ideal situations.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.11a
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• pp.33-35
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• 2018

기존의 사람간의 유사성 측정 시스템은 적외선 빔이나 열 감지 영상 장치를 통해 측정하였다. 하지만 이와 같은 방법으로 측정하면 2명 이상의 객체를 분류해내는 기술은 제공하지 않는다. 이에 본 논문은 고정된 카메라를 이용하여 각 사람의 피부색과 옷차림 등의 RGB 정보를 이용한 사람 유사성 측정 기법을 제안한다. RGB카메라 영상을 통하여 객체의 RGB 히스토그램을 얻은 후 각 객체에 대해 Bhattacharyya metric, Cosine similarity, Jensen difference, Euclidean distance로 histogram similarity를 계산하여 객체 추적 및 유사성 측정을 통해 객체를 분류한다. 제안된 시스템은 C/C++를 기반으로 구현하여, 유사성 측정 성능을 평가하였다.

• The Journal of Korean Association of Computer Education
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• v.17 no.2
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• pp.107-113
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• 2014

In this study, we design and implement an eye-gaze estimation system based on the extraction of eye contour and pupil region. In order to effectively extract the contour of the eye and region of pupil, the face candidate regions were extracted first. For the detection of face, YCbCr value range for normal Asian face color was defined by the pre-study of the Asian face images. The biggest skin color region was defined as a face candidate region and the eye regions were extracted by applying the contour and color feature analysis method to the upper 50% region of the face candidate region. The detected eye region was divided into three segments and the pupil pixels in each pupil segment were counted. The eye-gaze was determined into one of three directions, that is, left, center, and right, by the number of pupil pixels in three segments. In the experiments using 5,616 images of 20 test subjects, the eye-gaze was estimated with about 91 percent accuracy.

• The Journal of the Korea Contents Association
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• v.11 no.10
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• pp.1-10
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• 2011

In this paper, we proposed the skin color based hand and finger detection technology for the gesture recognition in CCTV surveillance. The aim of this paper is to present the methodology for hand detection and propose the finger detection method. The detected hand and finger can be used to implement the non-contact mouse. This technology can be used to control the home devices such as home-theater and television. Skin color is used to segment the hand region from background and contour is extracted from the segmented hand. Analysis of contour gives us the location of finger tip in the hand. After detecting the location of the fingertip, this system tracks the fingertip by using only R channel alone, and in recognition of hand motions to apply differential image, such as the removal of useless image shows a robust side. We explain about experiment which relates in fingertip tracking and finger gestures recognition, and experiment result shows the accuracy above 96%.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.4
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• pp.34-40
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• 2008

This paper presents a vision based walking robot control system using hand shape recognition. To recognize hand shapes, the accurate hand boundary needs to be tracked in image obtained from moving camera. For this, we use an active contour model-based tracking approach with mean shift which reduces dependency of the active contour model to location of initial curve. The proposed system is composed of four modules: a hand detector, a hand tracker, a hand shape recognizer and a robot controller. The hand detector detects a skin color region, which has a specific shape, as hand in an image. Then, the hand tracking is performed using an active contour model with mean shift. Thereafter the hand shape recognition is performed using Hue moments. To assess the validity of the proposed system we tested the proposed system to a walking robot, RCB-1. The experimental results show the effectiveness of the proposed system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.285-290
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• 2006

본 논문에서는 출입국자 관리의 효율성과 체계적인 출입국 관리를 위하여 여권 코드를 자동으로 인식하고 위조 여권을 판별할 수 있는 여권 인식 및 얼굴 인증 방법을 제안한다. 본 논문의 구성은 여권 인식과 얼굴 인증 부분으로 구성되며, 여권 인식 부분에서는 소벨 연산자, 수평 최소값 필터 등을 적용한 후, 8 방향 윤곽선 추적 알고리즘을 적용하여 코드의 문자열 영역을 추출하고 기울기를 보정한다. 추출된 문자열은 반복 이진화 방법을 적용하여 코드의 문자열 영역을 이진화 한다. 이진화된 문자열 영역에 대해 8 방향 윤곽선 추적 알고리즘을 적용하여 개별 코드를 추출한 후에 SOM(Self-Organizing Maps) 알고리즘을 적용하여 여권 코드를 인식한다. 얼굴 인증 부분에서는 여권 사진 영역의 특징을 이용하여 얼굴 후보 영역을 추출한 후, RGB와 YCbCr 색공간에서 피부색 정보를 이용하여 얼굴 영역을 추출한다. 추출된 얼굴 영역은 PCA(Principal Component Analysis) 알고리즘을 적용하여 특징 벡터를 구하고 여권 코드가 인식된 결과를 바탕으로 여권 소지자의 데이터 베이스에 있는 얼굴 영상의 특징벡터와의 거리 값을 계산하여 사진 위조 여부를 판별한다. 제안된 여권 인식 및 얼굴 인증 방법의 성능 평가를 위하여 원본 여권의 얼굴 부분을 위조한 여권과 기울어진 여권 영상을 대상으로 실험한 결과, 제안된 방법이 여권의 코드 인식 및 얼굴 인증에 있어서 우수한 성능이 있음을 확인하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.11a
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• pp.76-79
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• 2007

수화는 하나의 제스처가 하나의 단어를 나타내는 수화 단어와 한글을 알파벳으로 표현하는 지문자로 구성되어 있다. 본 논문에서는 USB 카메라로부터 촬영한 영상을 얻고 히스토그램을 이용하여 피부색 영역을 추출한다. 얼굴 영역 추적을 활용하여 이미지를 그리드화하고 지문자의 위치를 파악하여 초성, 중성, 종성을 구분하고 한글 음절을 구성하였다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.2
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• pp.20-32
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• 2010

Previous hardware devices to capture human motion have many limitations; expensive equipment, complexity of manipulation or constraints of human motion. In order to overcome these problems, real-time motion capture algorithms based on computer vision have been actively proposed. This paper presents an efficient analysis method of multiple view images for real-time motion capture. First, we detect the skin color regions of human being, and then correct the image coordinates of the regions by using camera calibration and epipolar geometry. Finally, we track the human body part and capture human motion using kalman filter. Experimental results show that the proposed algorithm can estimate a precise position of the human body.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.6
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• pp.44-56
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• 2008

Previous hardware devices to capture human motion have many limitations; expensive equipment, complexity of manipulation or constraints of human motion. In order to overcome these problems, real-time motion capture algorithms based on computer vision have been actively proposed. This paper presents an efficient analysis method of multiple view images for real-time motion capture. First, we detect the skin color regions of human being, and then correct the image coordinates of the regions by using camera calibration and epipolar geometry. Finally, we track the human body part and capture human motion using kalman filter. Experimental results show that the proposed algorithm can estimate a precise position of the human body.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.3
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• pp.1-10
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• 2010

As various interfacing devices for computational machines are being developed, a new HCI method using hand motion input is introduced. This interface method is a vision-based approach using a single camera for detecting and tracking hand movements. In the previous researches, only a skin color is used for detecting and tracking hand location. However, in our design, skin color and shape information are collectively considered. Consequently, detection ability of a hand increased. we proposed primary orientation edge descriptor for getting an edge information. This method uses only one hand model. Therefore, we do not need training processing time. This system consists of a detecting part and a tracking part for efficient processing. In tracking part, the system is quite robust on the orientation of the hand. The system is applied to recognize a hand written number in script style using DNAC algorithm. Performance of the proposed algorithm reaches 82% recognition ratio in detecting hand region and 90% in recognizing a written number in script style.