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

Sushil Kumar Mahapatra, Sumant Kumar Mohapatra, Sakuntala Mahapatra, S. K. Tripathy
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引用次数: 4

Abstract

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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一种用于水下鱼类检测的多线程模糊c均值算法
最近,科学家们需要知道水下鱼类种群的行为。以前使用的算法很多,但在处理复杂纹理和检测率较低的情况下存在问题。本文提出了一种多线程模糊c均值(MFC均值)方法来检测噪声和密集条件下的多运动鱼类。在该方法中,我们将多线程并行(MTP)方法与基于内核的光流方法相结合。提供了一个模糊c均值概念作为支持因素。仿真结果表明,该方法能够对水下鱼类进行跟踪和检测,具有较高的检测率。
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