[논문]Hand Segmentation Using Depth Information and Adaptive Threshold by Histogram Analysis with color Clustering

Fayya, Rabia; Rhee, Eun Joo

doi:10.9717/kmms.2014.17.5.547

[국내논문] Hand Segmentation Using Depth Information and Adaptive Threshold by Histogram Analysis with color Clustering 원문보기

멀티미디어학회논문지 = Journal of Korea Multimedia Society, v.17 no.5, 2014년, pp.547 - 555

Fayya, Rabia (Dept. of Computer Eng., Graduate School of Information and Communications, Hanbat National University) , Rhee, Eun Joo (Dept. of Computer Eng., Graduate School of Information and Communications, Hanbat National University)

Abstract ▼ AI-Helper

This paper presents a method for hand segmentation using depth information, and adaptive threshold by means of histogram analysis and color clustering in HSV color model. We consider hand area as a nearer object to the camera than background on depth information. And the threshold of hand color is adaptively determined by clustering using the matching of color values on the input image with one of the regions of hue histogram. Experimental results demonstrate 95% accuracy rate. Thus, we confirmed that the proposed method is effective for hand segmentation in variations of hand color, scale, rotation, pose, different lightning conditions and any colored background.

주제어

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문제 정의

This paper describes a method for adaptive hand segmentation of various Human races in different lighting conditions, including any colored background. Segmentation of hand having colored background is difficult, because the predefined threshold is dependent on background environment and lightning condition.

제안 방법

In this study, we propose a method for hand segmentation adaptively to solve the above mentioned problems for all colored races of images captured in any colored background and lightning condition. In order to solve the problem of colored background, we use depth information taken by stereo camera to extract hand area as nearer to the camera than background, and further objects are excluded as background [13-15].
The reason for obtaining high rate of good segmentation is that the proposed method is based on depth information and adaptive threshold by hue histogram analysis with color clustering. The depth information by stereo vision is used to exclude any colored background within disparity less than 200, and extract the hand area as the nearer object to the camera than background.

대상 데이터

The experimental data consisted of 189 sets of extracted hand using depth information. Samples of experiment data are shown in Fig.

이론/모형

Similar problems are found in work [4], where the background subtraction technique is used to segment hand from background in varying illumination that are controlled by grey world algorithm [5]. And skin is detected using Bayes method to estimate the skin and non-skin probability of pixels given in RGB color model. Anyhow, this method for hand detection is not enough to cover skin color in different illumination and colored background.

성능/효과

The result of the experiments showed the usefulness of the proposed method in segmentation of hand as well as the plain colored objects. Future work includes solving the problem of distinguishing between the hue similarity of hand and the outside of hand area.

참고문헌 (17)

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D. Xu, Y.L. Chen, X. Wu, Y. Ou, and Y. Xu, "Integrated Approach of Skin-color Detection and Depth Information for Hand and Face Localization," IEEE International Conference on Robotics and Biomimetics, pp. 952-956, 2011.
T.C. Pham, X.D. Pham, D.D. Nguyen, S.H. Jin, and, J.W. Jeon, "Dual Hand Extraction using Skin Color and Stereo Information," IEEE International Conference on Robotics and Biomimetics, pp. 330-335, 2009.
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G. Chang, J. Park, C. Oh, and C. Lee, "A Decision Tree based Real-time Hand Gesture Recognition Method using Kinect," Journal of Korea Multimedia Society, Vol. 16, No. 12, pp. 1393-1402, 2013.

원문보기 상세보기
B.S. Lee and E.J. Rhee, "Pixel-based Skin Color Detection using the Ratio of H to R in Color Image," Journal of Information of technology Applications & Management, Vol. 12, No. 1, pp. 231-239, 2005.
G.R. Bradski and V. Pisarevsky, "Intel's Computer Vision Library: Applications in Calibration, Stereo Segmentation, Tracking, Gesture, Face and Object Recognition," Proceeding of the IEEE Conference on Computer Vision and Pattern Recognition, Vol. 2, pp. 796-797, 2000.

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[국내논문] Hand Segmentation Using Depth Information and Adaptive Threshold by Histogram Analysis with color Clustering 원문보기

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[국내논문] Hand Segmentation Using Depth Information and Adaptive Threshold by Histogram Analysis with color Clustering 원문보기

Abstract ▼ AI-Helper

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참고문헌 (17)

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