Static Gesture Recognition Algorithm Based on Upper Triangular Image Texture and Recursive Graph


  • Cai Yang School of Computer and Information Technology, Nanyang Normal University,



contour sequence, image texture, normalized feature vector, static gesture recognition, upper triangular.


A static gesture recognition algorithm is proposed based on a recursive graph of the upper triangular image texture, motivated by the low accuracy and robustness of existing algorithms. Firstly, the fingertip localization method based on contour curvature is used to obtain the palm region and then the gesture contour model is established. Secondly, a recurrence plot of the gesture contour sequence is built, which is constructed using the central point and the starting point coordinates. Finally, the texture recognition algorithm is applied to calculate the normalized distance between the recurrence plots of the gesture. The experimental results show that the proposed algorithm can achieve higher recognition accuracy under varying complex backgrounds and illumination. At the same time, when the gesture is in rotation, translation, or scaling, the algorithm has high robustness with a small amount of computation and high efficiency.


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Author Biography

Cai Yang, School of Computer and Information Technology, Nanyang Normal University,

School of Computer and Information Technology


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How to Cite

Yang, C. (2017). Static Gesture Recognition Algorithm Based on Upper Triangular Image Texture and Recursive Graph. Journal of Engineering and Technological Sciences, 49(3), 373-387.