A Proposed Multithreading Fuzzy C-Mean Algorithm for Detecting Underwater Fishes

2016 2nd International Conference on Computational Intelligence and Networks (CINE)(2016)

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摘要
Recently, Scientists needs to know the behavior of fish populations in underwater. Previously many algorithms are used but they are suffered in complex textures and low detection rate. This paper proposed a multi threading fuzzy c-mean (MFC mean) approach to detect multi-moving fishes in a noisy and dense condition. In this approach, we combines the multi threaded parallel (MTP) approach and kernel based approach for optical flow. A fuzzy c-mean concept provided as a supporting factor. The simulation results show that the proposed method can able to track and detect underwater fishes with high detection rate.
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关键词
tracking,fish,underwater,detection rate,fuzzy c-mean,kernel approach
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