Hand gesture recognition algorithm combining hand-type adaptive algorithm and effective-area ratio for efficient edge computing

Hand is a highly variable organ and hand features are easily affected by environmental factors. Considering the characteristics of hand gesture, a novel hand gesture recognition algorithm based on hybrid moments is presented. First, According to the color cue, the hand shape is available to extract from the complicated background, then the contour moment invariant and Fourier Descriptor are extracted and fused into a hybrid feature, finally the hybrid feature are put into the BP network to identity. The experimental results show that the method has better robustness and higher recognition rate.

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Hand Gesture Recognition Algorithm: A Real-Time Human-Body-Based Approach

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.303-306.1338 ◽

2013 ◽

Vol 303-306 ◽

pp. 1338-1343

Author(s):

Xin Xiong Li ◽

Yi Xiong ◽

Zhi Yong Pang ◽

Di Hu Chen

Keyword(s):

Real Time ◽

Gesture Recognition ◽

Human Body ◽

Skin Color ◽

Average Rate ◽

Vital Role ◽

Recognition Algorithm ◽

Hand Gesture Recognition ◽

High Tech ◽

Hand Gesture

Despite the appearance of high-tech human computer interface (HCI) devices, pattern recognition and gesture recognition with single camera are still playing vital role in research. A real-time human-body based algorithm for hand gesture recognition is proposed in this paper. The basis of our approach is a combination of moving object segmentation process and skin color detector based on human body structure to obtain the moving hands from input images, which is able to deal with the problem of complex background and random noises, and a rotate correction process for better finger detection. With ten fingers detected, more than 1000 gestures can be recognized before concerning motion paths. This paper includes experimental results of five gestures, which can be extended to other conditions. Experiments show that the algorithm can achieve a 99 percent recognition average rate and is suitable for real-time applications.

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A Real Time Hand Gesture Recognition System Based on DFT and SVM

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.284-287.3004 ◽

2013 ◽

Vol 284-287 ◽

pp. 3004-3009 ◽

Cited By ~ 2

Author(s):

Wen Her Chen ◽

Ching Tang Hsieh ◽

Tsun Te Liu

Keyword(s):

Gesture Recognition ◽

Skin Color ◽

Recognition System ◽

Extraction Process ◽

Recognition Algorithm ◽

Hand Gesture Recognition ◽

Hand Gesture ◽

Fast Detection ◽

Starting Point ◽

Boundary Deformation

Vision based band gesture recognition provides a more nature and powerful means for human-computer interaction. A fast detection process of hand gesture and an effective feature extraction process are presented. The proposed a hand gesture recognition algorithm comprises four main steps. First use Cam-shift algorithm to track skin color after closing process. Second, in order to extract feature, we use BEA to extract the boundary of the hand. Third, the benefits of Fourier descriptor are invariance to the starting point of the boundary, deformation, and rotation, and therefore transform the starting point of the boundary by Fourier transformation. Finally, outline feature for the nonlinear non-separable type of data was classified by using SVM. Experimental results showed the accuracy is 93.4% in average and demonstrated the feasibility of proposed system.

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