Paper
2 February 2009 PSO based Gabor wavelet feature extraction and tracking method
Hongguang Sun, Qian Bu, Huijie Zhang
Author Affiliations +
Abstract
The paper is the study of 2D Gabor wavelet and its application in grey image target recognition and tracking. The new optimization algorithms and technologies in the system realization are studied and discussed in theory and practice. Optimization of Gabor wavelet's parameters of translation, orientation, and scale is used to make it approximates a local image contour region. The method of Sobel edge detection is used to get the initial position and orientation value of optimization in order to improve the convergence speed. In the wavelet characteristic space, we adopt PSO (particle swarm optimization) algorithm to identify points on the security border of the system, it can ensure reliable convergence of the target, which can improve convergence speed; the time of feature extraction is shorter. By test in low contrast image, the feasibility and effectiveness of the algorithm are demonstrated by VC++ simulation platform in experiments. Adopting improve Gabor wavelet method in target tracking and making up its frame of tracking, which realize moving target tracking used algorithm, and realize steady target tracking in circumrotate affine distortion.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hongguang Sun, Qian Bu, and Huijie Zhang "PSO based Gabor wavelet feature extraction and tracking method", Proc. SPIE 7160, 2008 International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Applications, 71602W (2 February 2009); https://doi.org/10.1117/12.808065
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Wavelets

Particle swarm optimization

Detection and tracking algorithms

Feature extraction

Image filtering

Image processing

Optimization (mathematics)

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