Browse > Article
http://dx.doi.org/10.14372/IEMEK.2019.14.6.295

Color-Based Real-Time Hand Region Detection with Robust Performance in Various Environments  

Hong, Dong-Gyun (Daegu University.)
Lee, Donghwa (Daegu University.)
Publication Information
IEMEK Journal of Embedded Systems and Applications / v.14, no.6, 2019 , pp. 295-311 More about this Journal
Abstract
The smart product market is growing year by year and is being used in many areas. There are various ways of interacting with smart products and users by inputting voice recognition, touch and finger movements. It is most important to detect an accurate hand region as a whole step to recognize hand movement. In this paper, we propose a method to detect accurate hand region in real time in various environments. A conventional method of detecting a hand region includes a method using depth information of a multi-sensor camera, a method of detecting a hand through machine learning, and a method of detecting a hand region using a color model. Among these methods, a method using a multi-sensor camera or a method using a machine learning requires a large amount of calculation and a high-performance PC is essential. Many computations are not suitable for embedded systems, and high-end PCs increase or decrease the price of smart products. The algorithm proposed in this paper detects the hand region using the color model, corrects the problems of the existing hand detection algorithm, and detects the accurate hand region based on various experimental environments.
Keywords
Hand image processing; Image processing; Real-time performance; Background subtraction;
Citations & Related Records
Times Cited By KSCI : 10  (Citation Analysis)
연도 인용수 순위
1 O.E. Seok, C.J. Hak, "Analyzing Users & Quot; Behaviors and Needs of Mirror for UX Design of Smart Mirror at Fashion Store," Journal of Digital Design, Vol. 15, No. 3, pp. 861-870, 2015 (in korean).   DOI
2 S.H. Lee, E.H. Kim, U.C. Lee, "Strategies for Designing Smart Computing Technology to Improve Users Behaviors and Lifestyle," Investigation Research, pp. 1-224, 2015 (in Korean).
3 H.H. Park, J.Y. Choi, J.I. Park, K.S. Moon, "A Study on Hand Region Detection for Kinect-based Hand Region Detection for Kinect-based Hand Shape Recognition," Journal of the Broadcast Engineering, Vol. 18, No. 3, pp. 393-400, 2013 (in Korean).   DOI
4 J.H. Seo, S.H. Chae, J.W. Shim, H.Y. Kim, T.D. Han, "Region-growing Based Hand Segmentation Algorithm Using Skin Color and Depth Information," Journal of Korea Multimedia Society, Vol. 16, No. 9, pp. 1031-1043, 2013 (in Korean).   DOI
5 Y.Y. Choi, J. Tang, S.E. Jang, S.W. Kim, "User Customizable Hit Action Recognition Method Using Kinect," Journal of Korea Multimedia Society, Vol. 18, No. 4, pp. 557-564, 2015 (in Korean).   DOI
6 S.I. Joo, S.H. Weon, H.I. Choi, "Hand Region Tracking and Fingertip Detection Based on Depth Image," Journal of the Korea Society of Computer and Information, Vol. 18, No. 8, pp. 65-75, 2013 (in Korean).   DOI
7 S.H. Park, J.R. Kim, J.S. Kim, S.Y. Lee, "Hand Detection Using Depth Information," Journal of The Korean Society of Broad Engineers, pp. 299-300, 2011 (in Korean).
8 M.S. Park, S.H. Kang, O.S. Chae, "Robust Hand Detection and Tracking Using Sensor Fusion," Journal of Korean Institute of Information Scientists and Engineers : Software and Applications, Vol. 40, No. 9, pp. 558-566, 2013 (in Korean).
9 J.H. Baek, J.S. kim, C.Y. Yoon, D.Y. Kim, E.T. Kim, "Part-based Hand Detection Using HOG," Journal of Korean Institute of Intelligent Systems, Vol. 23, No. 6, pp. 551-557, 2013 (in Korean).   DOI
10 J.H. Baek, J.S. Kim, C.Y. Yoon, D.Y. Kim, E.T. Kim, "Gesture Recognition Using Part-based Dual HOG-SVM," Journal of Korean institute of intelligent systems, Vol. 24, No. 1, pp. 129-130, 2014 (in Korean).   DOI
11 B.S. Moon, D.W. Kim, "User Specified Gesture Recognition Method Using Corrected Machine Learning," Journal of the Institute of Electronics and Information Engineers, Vol. 56, No. 1, pp. 57-68, 2019 (in Korean).   DOI
12 S.J. Lee, R.W. Kang, W.S. Ju, S.J. Ahn, J.J. Lee, "Hand Region Detection and Tracking Based on HSI Color Model," Journal of the Korean Multimedia Society, pp. 553-556, 2006 (in Korean).
13 J.H. Park, D.S. Kang, "Proposal of Hand Mouse Interface Using Separated Finger Recognition of Distance Transform Vector Based," The Journal of Korean Institute of Information Technology, Vol. 12, No. 1, pp. 31-37, 2014 (in Korean).
14 J.H. Yoo, D.S. Kang, "A Study on Real-time Processing for Hand Region Detection Using Modified PGF at an Image Segmentation Algorithm," Journal of Korean Institute of Information Technology, Vol. 10, No. 12, pp. 173-178, 2012 (in Korean).
15 S.H. Chae, K.K. Jun, "HSV Color Model Based Hand Contour Detector Robust to Noise," Journal of Korea Multimedia Society, Vol. 18, No. 10, pp. 1149-1156, 2015 (in Korean).   DOI
16 E.C. Choi, J.Y. Kim, J.W. Lee, J.G. Lim, "Palm Area Detection by Maximum Hand Width," Journal of the Korea Contents Association, Vol. 18, No. 4, pp. 398-405, 2018 (in Korean).   DOI
17 C.S Lee, S.Y. Chun, S. W. Park, "Electric Board Interface Using Hand Shape Detection and Tracking," Proceedings of Human Computer Interaction, pp. 291-293, 2012 (in Korean).
18 M.Y. Na, H.J. Kim, T.Y. Kim, "An Illumination and Background-robust Hand Image Segmentation Method Based on the Dynamic Threshold Values," Journal of Korea Multimedia Society, Vol. 14, No. 5, pp. 607-613, 2011 (in Korean).   DOI
19 C.M. Kim, K.W. Lee, "Implementation of Motion Detection Based on Extracting Reflected Light Using 3-successive Video Frames," Journal of Korean Institute of Information Scientists and Engineers Transactions on Computing Practices, Vol. 22, No. 3, pp. 133-138, 2016 (in Korean).
20 Y. Xu, J. Dong, B. Zhang, D. Xu, "Background Modeling Methods in Video Analysis: A Review and Comparative Evaluation," Chinese Association for Artificial Intelligence Transactions on Intelligence Technology, Vol. 1, No. 1, pp. 43-60, 2016.
21 M.A. Mousse, E.C. Ezin, C. Motamed, "Foreground-background Segmentation Based on Codebook and Edge Detector," Proceedings of IEEE Conference on Signal Image Technology and Internet Based Systems, pp. 119-124, 2014.
22 Y.J. Kim, "An Improved Adaptive Background Mixture Model for Real-time Object Tracking Based on Background Subtraction," Journal of the Korea Society of Computer and Information, Vol. 10, No. 6, pp.187-193, 2005 (in Korean).
23 J.S. Oh, S.K. Lee, "Improved MOG Algorithm Based on Adaptive Threshold for Effective Background Classification," Journal of Arts and Imaging Science, Vol. 1, No. 4, pp. 54-59, 2014 (in Korean).
24 D.G. Kim, "Moving Object Detection Using Gaussian Pyramid Based Subtraction Images in Road Video Sequences," Journal of the Korea Academia-Industrial Cooperation Society, Vol. 12, No. 12, pp. 5856-5864, 2011 (in Korean).   DOI
25 J.M. Jeong, J.Y. Choi, "Adaptive Background Modeling Considering Stationary Object and Object Detection Technique Based on Multiple Gaussian Distribution," Journal of the Korea Society of Computer and Information, Vol. 23, No. 11, pp. 51-57, 2018 (in Korean).   DOI
26 K.P. Gwon, J.H. Yoo, "Numeric Sign Language Interpreting Algorithm Based on Hand Image Processing," IEMEK J. Embed. Sys. Appl., Vol. 14, No. 3, pp. 133-142, 2019 (in Korean).   DOI
27 H.A. Kim, C.W. Lee, "Detection Accuracy Improvement of Hang Region using Kinect," Journal of the Korea Institute of Information and Communication Engineering, Vol. 18, No. 11, pp. 2727-2732, 2014 (in Korean)   DOI
28 J.H. Seo, S.H. Chea, J.W. Shim, H.Y. Kim, T.D. Han, "Region-growing Based Hand Segmentation Algorithm Using Skin Color and Depth Information," Journal of Korea Multimedia Society, Vol. 16, No. 9, pp. 1031-1043, 2013 (in Korean)   DOI
29 Avaliable on : https://en.wikipedia.org/wiki/YUV/