IJIGSP Vol. 11, No. 9, 8 Aug. 2019
Cover page and Table of Contents: PDF (size: 960KB)
Full Text (PDF, 960KB), PP.25-33
Views: 0 Downloads: 0
Hand Detection, Hand Gesture Recognition, Colour Segmentation, Human Computer Interaction
The hand gesture recognition system is the hottest topic for the human-machine interaction and computer vision fields. The hand gesture recognition system is still a challenging research area in computer vision for human-computer interaction because of various device conditions, various illumination effects, and very complex background. The recognition of hand gestures used in various application areas: such as sign language recognition, man-machine interaction, human-robot interaction, and intelligent device control and many other application areas. The robust detection of hand in hand gesture recognition system has become a challenging task due to clutter background, dynamic background, and various illumination conditions in real-world conditions. Segmentation is the partioning/separating the foreground hand region from the background region in an image. Segmentation is also pre-processing steps of the hand gesture recognition system. The recognition accuracy will increase if the hand region correctly detected. So, hand region detection is the main important step for the hand gesture recognition system.
Phyu Myo Thwe, May The` Yu, "Analysis on Skin Colour Model Using Adaptive Threshold Values for Hand Segmentation", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.11, No.9, pp. 25-33, 2019. DOI: 10.5815/ijigsp.2019.09.03
[1]K. B. Shaik, P. Ganesan, V. Kalist, B. S. Sathish, & J. M. M Jenitha (2015). Comparative study of skin color detection and segmentation in HSV and YCbCr color space. Procedia Computer Science, 57, 41-48.
[2]T.J. McBride, N.Vandayar, K.J.Nixon (2019). A Comaprison of Skin Detection Algorithm for Hand Gestrue Recognition.
[3].D.H Nguyen, T.H. Le, T.H.Tran, H. Vu, T.L.Le, H.G. Doan (2018, October). Hand segmentation under different viewpoints by combination of Mask R-CNN with tracking. In 2018 5th Asian Conference on Defense Technology (ACDT)(pp. 14-20). IEEE.
[4]Q.Zhang, M. Yang, K.Kpalma, Q.Zheng, X.Zhang (2018). Segmentation of Hand Posture against Complex Backgrounds Based on Saliency and Skin Colour Detection. IAENG International Journal of Computer Science, 45(3).
[5]R. F. Rahmat, T. Chairunnisa, D. Gunawan, & O. S. Sitompul (2016, August). Skin color segmentation using multi-color space threshold. In 2016 3rd International Conference on Computer and Information Sciences (ICCOINS) (pp. 391-396). IEEE.
[6]S. Thakur, S. Paul, A. Mondal, S. Das, & A. Abraham (2011, December). Face detection using skin tone segmentation. In 2011 World Congress on Information and Communication Technologies (pp. 53-60). IEEE.
[7]S. L. Phung, A. Bouzerdoum, & D. Chai (2005). Skin segmentation using color pixel classification: analysis and comparison. IEEE Transactions on Pattern Analysis & Machine Intelligence, (1), 148-154.
[8]S. L. Phung, A. Bouzerdoum, & D. Chai (2003, July). Skin segmentation using color and edge information. In Seventh International Symposium on Signal Processing and Its Applications, 2003. Proceedings. (Vol. 1, pp. 525-528). IEEE.
[9]G. Kukharev, & A. Nowosielski (2004). Visitor identification-elaborating real time face recognition system.
[10]D. Chai, & K. N. Ngan (1999). Face segmentation using skin-color map in videophone applications. IEEE Transactions on circuits and systems for video technology, 9(4), 551-564.
[11]Y. Xu, & G. Pok, (2017). Identification of Hand Region Based on YCgCr Color Representation. International Journal of Applied Engineering Research, 12(6), 1031-1034.
[12]W. Wang, & J. Pan (2012, July). Hand segmentation using skin color and background information. In 2012 International Conference on Machine Learning and Cybernetics (Vol. 4, pp. 1487-1492). IEEE.
[13]S. Patidar, & D. C. Satsangi (2013). Hand segmentation and tracking technique using color models. International Journal of Software & Hardware Research in Engineering, 1(2), 18-22.
[14]S. Rungruangbaiyok, R. Duangsoithong, & K. Chetpattananondh (2015, June). Ensemble Threshold Segmentation for hand detection. In 2015 12th International Conference on Electrical Engineering/ Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)(pp. 1-5). IEEE.
[15]X. Yingxin, L. Jinghua, W. Lichun, & K. Dehui (2016, December). A robust hand gesture recognition method via convolutional neural network. In 2016 6th International Conference on Digital Home (ICDH) (pp. 64-67). IEEE.
[16]M. R Tabassum, A. U. Gias, M. Kamal, H. M. Muctadir, M. Ibrahim, A. K. Shakir, & M. Islam (2010). Comparative study of statistical skin detection algorithms for sub-continental human images. arXiv preprint arXiv:1008.4206.
[17]L. Y. Deng, J. C. Hung, H. C. Keh, K. Y. Lin, Y. J., & N. C. Huang, (2011). Real-time hand gesture recognition by shape context based matching and cost matrix. Journal of networks, 6(5), 697.
[18]U. Ahlvers, R. Rajagopalan, & U. Zölzer (2005, September). Model-free face detection and head tracking with morphological hole mapping. In 2005 13th European Signal Processing Conference (pp. 1-4). IEEE.
[19]D. L. Lee & W. S. You (2017). Recognition of complex static hand gestures by using the wristband-based contour features. IET Image Processing, 12(1), 80-87.
[20]J. Sahoo, S. Ari, & D. Ghosh (2018). Hand Gesture Recognition using DWT and F-ratio Based Feature Descriptor. IET Image Processing.
[21]Z. Qiu-yu, L. Jun-chi, Z. Mo-yi, D. Hong-xiang, & L. Lu (2015). Hand gesture segmentation method based on YCbCr color space and K-means clustering. International Journal of Signal Processing, Image Processing and Pattern Recognition, 8(5), 105-116.