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The Application and Research of Image Processing Based on Particle Swarm Optimization

Author: HuPingPing
Tutor: PeiZhenKui
School: China University of Petroleum
Course: Computer Software and Theory
Keywords: particle swarm optimization image segmentation kernel fuzzy c-means clustering Digital watermarking Discrete Cosine Transform
CLC: TP391.41
Type: Master's thesis
Year: 2008
Downloads: 162
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Abstract


Particle swarm optimization algorithm is a heuristic global optimization algorithm which appeared recently. It has been widely concerned by people because of its feasibility and effectiveness. It has been proven to be a powerful competitor to other heuristic algorithms, such as genetic algorithm, taboo search and simulated annealing algorithm for global optimization problems. The base idea of this theory is from the colony behaviors of birds. The merit of PSO is that it can assure the particles land the best place with some simple rules. So this method has the attribute of intelligence and society partly.Based on the PSO’s idea, the PSO has been introduced and discussed in detail in this paper. The merits and disadvantages of the PSO are analyzed and then its basal principle is analyzed and researched in this paper. In order to prove algorithm’s performance, two novel algorithms are improved. One is Fuzzy clustering algorithm which uses the merits of the global optimizing and higher convergent speed of Particle Swarm Optimization (PSO) algorithm and combines with Kernel Fuzzy C-Means (KFCM) is proposed. In general, traditional clustering algorithms are suitable to implement clustering only if the feature differences of data are large. If the feature differences are small and even cross in the original space, it is difficult for traditional algorithms to cluster correctly. By using Gauss kernel functions, we can map the data in the original space to a high dimensional feature space in which we can perform clustering efficiently. The algorithm eliminates KFCM trapped local optimum, being sensitive to initial data and the noise data. The performance of this modified PSO-KFCM is compared with KFCM. The results of simulation experiments on medical image show the feasibility and effectiveness of the new clustering algorithm. Another is watermarking scheme on PSO in the DCT domain. Digital watermarking has recently been proposed as a new means to provide copyright protection of multimedia data and image authentication. Along with penetrated analyze of the theory of PSO, an innovative watermarking scheme on PSO in the DCT domain is proposed. Computer simulation indicates this scheme can find an optimized DCT domain frequency bands when we embed an watermarking image into an digital image. Simulation results prove the balance of conflicting between the invisibility and robustness. Attacking experiment results reveal the fact that the scheme is robust to JPEG compression, noise, et al.Finally, the developing foreground and correlative application engineering technology are introduced. The research trend and PSO in the future are pointed out in some areas.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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