Design of a hand-shape acquisition and recognition system based on DSP

Wenwen Li; Fu Liu; Lei Gao

doi:10.1117/12.2031374

26 October 2013 Design of a hand-shape acquisition and recognition system based on DSP

Wenwen Li, Fu Liu, Lei Gao

Proceedings Volume 8921, MIPPR 2013: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications; 89211D (2013) https://doi.org/10.1117/12.2031374
Event: Eighth International Symposium on Multispectral Image Processing and Pattern Recognition, 2013, Wuhan, China

Abstract

In this paper, we design a hand-shape image acquisition and processing system based on DSP for solving the problem of hand-shape recognition. Acquisition configuration was designed, and the key parts (encoder, decoder, memory chip etc.) are selected. And a new method for hand-shape recognition based on wavelet moment is presented to overcome some shortage in present method for hand shape recognition. Firstly, image processing including binary processing and segment of hand silhouette are used, and then translation and scale normalization algorithms is implemented on the palms and fingers image. After that the wavelet moment characteristics of image are extracted. At last, support vector is achieved by training 100 images data in images database, 10 testing images were selected randomly to verify validity and feasibility of algorithms. Experimental results indicate that the 10 testing images are all classified correctly. The new method of extracting hand shape wavelet moment as characteristic matrix is easy to realize with characteristic of high utility and accuracy, and solve the problem of translation, rotation and scaling during the image acquisition process without positioning aids.

Citation Download Citation

Wenwen Li, Fu Liu, and Lei Gao "Design of a hand-shape acquisition and recognition system based on DSP", Proc. SPIE 8921, MIPPR 2013: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 89211D (26 October 2013); https://doi.org/10.1117/12.2031374

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KEYWORDS

Digital signal processing

Image processing

Wavelets

Image acquisition

Image segmentation

Feature extraction

Databases

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