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Vol. 169, Issue 4, April 2014, pp. 67-72




The Research and Application of SURF Algorithm Based on Feature Point
Selection Algorithm

1 Zhang Fang Hu, 2 Lin Yang, 2 Luan Luo, 2 Yi Zhang, 3 Xiao Chuan Zhou

1 Key Laboratory of Optical Fiber Communication Technology Chongqing Education Commission, Chongqing University of Post and Telecommunications, Chongqing 400065, P. R. China
2 Research Center of Intelligent System and Robot, Chongqing University of Post and Telecommunications,
Chongqing 400065, P. R. China
3 China Petroleum Pipeline Telecommunication & Electricity Engineering Corporation,
Langfang City of Hebei province, 065000, P. R. China
1 Tel.: +86-18725875566

1 E-mail: huzf@cqupt.edu.cn


Received: 26 January 2014 /Accepted: 27 March 2014 /Published: 30 April 2014

Digital Sensors and Sensor Sysstems


Abstract: As the pixel information of depth image is derived from the distance information, when implementing SURF algorithm with KINECT sensor for static sign language recognition, there can be some mismatched pairs in palm area. This paper proposes a feature point selection algorithm, by filtering the SURF feature points step by step based on the number of feature points within adaptive radius r and the distance between the two points, it not only greatly improves the recognition rate, but also ensures the robustness under the environmental factors, such as skin color, illumination intensity, complex background, angle and scale changes. The experiment results show that the improved SURF algorithm can effectively improve the recognition rate, has a good robustness.


Keywords: Sign language alphabet, Feature point selection algorithm, Adaptive radius, Improved speed up robust features algorithm.


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