• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1718-1720
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• 2013

본 논문에서는 다중 손 끝점 검출을 위해 특징 추출 기법 및 이를 기반으로 한 손 끝점 검출 알고리즘을 제안한다. 특징 추출을 위해 Local Binary Feature(LBP)을 사용하였고 특징의 차원을 축소하기 위해 Principal Component Analysis(PCA) 기법을 이용하였다. 손 끝점 판별을 위해 Reduced multivariate polynomial Model(RM) Classifier를 사용하여 실험 결과 제안된 손 끝점 검출 기법이 다양한 환경에서 동작 하는 것을 확인 하였다.

• Journal of Korea Multimedia Society
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• v.13 no.2
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• pp.316-323
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• 2010

In this paper, we propose fingertip extraction and hand motion recognition method for augmented reality applications. First, an input image is transformed into HSV color space from RGB color space. A hand area is segmented using double thresholding of H, S value, region growing, and connected component analysis. Next, the end points of the index finger and thumb are extracted using morphology operation and subtraction for a virtual keyboard and mouse interface. Finally, the angle between the end points of the index finger and thumb with respect to the center of mass point of the palm is calculated to detect the touch between the index finger and thumb for implementing the click of a mouse button. Experimental results on various input images showed that our method segments the hand, fingertips, and recognizes the movements of the hand fast and accurately. Proposed methods can be used the input interface for augmented reality applications.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.167-173
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• 2015

Extraction of Finger-end points is one of the most process for user multi-commands in the Hand-Gesture interface technology. However, most of previous works use the geometric and morphological method for extracting a finger-end points. Therefore, this paper proposes the method of user finger-end points extraction that is motivated a ultrared diffused illumination, which is used for the user commands in the multi-touch display device. Proposed air-mouse is worked by the quantity state and moving direction of extracted finger-end points. Also, our system includes a basic mouse event, as well as the continuous command function for expending a user multi-gesture. In order to evaluate the performance of the our proposed method, after applying to the web browser application as a command device. As a result, the proposed method showed the average 90% success-rate for the various user-commands.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10b
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• pp.49-53
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• 2006

본 논문에서는 복잡한 배경을 가진 영상에서 손 영역을 안정적으로 검출, 손 형상을 인식하여 그림 맞추기 응용 프로그램을 제어하는 시스템에 대해 기술한다. 피부색의 컬러 정보를 이용하여 손 영역만을 추출한 후 핑거 팁 템플릿매칭을 사용하여 손가락 끝점을 찾아낸다. 또한 손 영역의 에지 방향성 히스토그램을 구하여 얻어진 정보를 바탕으로 주성분 분석법을 사용하여 손 형상을 인식한다. 최종적으로 인식된 손 형상 정보와 손가락 끝점 추적을 이용한 명령어 실행으로 그림 맞추기 응용 프로그램을 제어 한다. 본 논문에서 제안한 알고리즘으로 그림 맞추기 응용 프로그램 제어에 적용한 결과 안정적인 실험 결과를 얻을 수 있었고, HCI 분야에서 다양하게 활용될 수 있음을 확인하였다.

• Journal of the Korea Society of Computer and Information
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• v.18 no.8
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• pp.65-75
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• 2013

This paper proposes a method of tracking the hand region and detecting the fingertip using only depth images. In order to eliminate the influence of lighting conditions and obtain information quickly and stably, this paper proposes a tracking method that relies only on depth information, as well as a method of using region growing to identify errors that can occur during the tracking process and a method of detecting the fingertip that can be applied for the recognition of various gestures. First, the closest point of approach is identified through the process of transferring the center point in order to locate the tracking point, and the region is grown from that point to detect the hand region and boundary line. Next, the ratio of the invalid boundary, obtained by means of region growing, is used to calculate the validity of the tracking region and thereby judge whether the tracking is normal. If tracking is normal, the contour line is extracted from the detected hand region and the curvature and RANSAC and Convex-Hull are used to detect the fingertip. Lastly, quantitative and qualitative analyses are performed to verify the performance in various situations and prove the efficiency of the proposed algorithm for tracking and detecting the fingertip.

• 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 IKEEE
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• v.18 no.4
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• pp.478-484
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• 2014

In this paper, we propose new algorithm for positioning of mouse cursor using fingertip direction on kinect depth camera. The proposed algorithm uses center of parm points from distance transform when fingertip point toward screen. Otherwise, algorithm use fingertip points. After image preprocessing, the center of parm points is calculated from distance transform results. If the direction of the finger towards the camera becomes close to the distance between the fingertip point and center of parm point, it is possible to improve the accuracy of positioning by using the center of parm point. After remove arm on image, the fingertip points is obtained by using a pixel on the long distance from the center of the image. To calculate accuracy of mouse positioning, we selected any 5 points. Also, we calculated error rate between reference points and mouse points by performed 500 times. The error rate results could be confirmed the accuracy of our algorithm indicated an average error rate of less than 11%.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06c
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• pp.516-520
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• 2010

컴퓨터와 인간과의 상호작용에서 다양한 형태의 인터페이스에 대한 요구가 날로 커지고 있다. 그 가운데 실생활에서도 사물을 지칭하거나 의사소통의 수단으로 사용되는 손과 관련한 인터페이스에 대한 연구가 주목 받고 있다. 기존의 대부분의 연구들은 손을 입력 받으면 영상을 기반으로 손의 중심점을 찾아 그것의 위치를 인식하였는데 이는 물체에 의해 손이 가려진 것과 같이 잘못된 영상을 입력 받았을 때 원하는 결과를 얻지 못하는 상황을 야기할 수 있다. 본 논문은 이러한 점을 보완하기 위하여 손의 중심점을 찾을 때 방해 받는 물체에 덜 민감하게 반응하도록 칼만 필터를 적용하여 문제점을 개선할 수 있도록 하였다. 또한 결과의 정확도를 높일 수 있도록 손가락 끝점을 추출하여 칼만 필터의 매개변수에 반영시켜주었다. 그 결과 예기치 못한 상황이 발생했을 때에도 이것에 덜 민감하게 반응하면서 손의 위치를 비교적 정확하게 측정할 수 있었으며 시스템의 과정이 간단하여 실시간으로 응용하기에 적합한 것을 알 수 있었다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.7
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• pp.1686-1694
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• 2014

In this paper, a new scheme to recognize a finger shape in the depth image captured by Kinect is proposed. Rigid transformation of an input finger shape is pre-processed for its robustness against the shape angle of input fingers. After extracting contour map from hand region, observing the change of contour pixel location is performed to calculate rotational compensation angle. For the finger shape recognition, we first acquire three pixel points, the most left, right, and top located pixel points. In the proposed algorithm, we first acquire three pixel points, the most left, right, and top located pixel points for the finger shape recognition, also we use geometrical features of human fingers such as Euclidean distance, the angle of the finger and the pixel area of hand region between each pixel points to recognize the finger shape. Through experimental results, we show that the proposed algorithm performs better than old schemes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.3
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• pp.636-642
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• 2017

In this paper, We proposed a novel hand-gesture recognition algorithm using concentric-circle expanding and tracing. The proposed algorithm determines region of interest of hand image through preprocessing the original image acquired by web-camera and extracts the feature of hand gesture such as the number of stretched fingers, finger tips and finger bases, angle between the fingers which can be used as intuitive method for of human computer interaction. The proposed algorithm also reduces computational complexity compared with raster scan method through referencing only pixels of concentric-circles. The experimental result shows that the 9 hand gestures can be recognized with an average accuracy of 90.7% and an average algorithm execution time is 78ms. The algorithm is confirmed as a feasible way to a useful input method for virtual reality, augmented reality, mixed reality and perceptual interfaces of human computer interaction.