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Hierarchical codebook for moving microbe detection in sewage

机译:污水中移动微生物检测的层次码本

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In this paper, we propose a newly object detection method for moving microbe in sewage. Firstly, two codebooks with YCrCb color model and improved local direction pattern are introduced in spatial context. Then, we design an adaptive update mechanism to accelerate convergence and enhance the accuracy of background based on self-learning strategy. Finally, we construct spatial and temporal relations in a MRF-MAP framework to further eliminate the left background pixels in foreground. Experiments results have showed the effectiveness and stability of our proposed method, compared with other algorithms.
机译:在本文中,我们提出了一种新的目标物检测方法,用于检测污水中的微生物。首先,在空间环境中介绍了两种具有YCrCb颜色模型和改进的局部方向图的密码本。然后,我们基于自学习策略设计了一种自适应更新机制,以加快收敛速度​​并提高背景精度。最后,我们在MRF-MAP框架中构建时空关系,以进一步消除前景中的左背景像素。实验结果表明,与其他算法相比,该方法的有效性和稳定性。

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