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Features extraction based on fuzzy clustering and segmentation onto the motion region for medium field surveillance application

机译:基于模糊聚类和运动区域分割的特征提取在中场监控中的应用

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摘要

Fuzzy-based clustering algorithm is becoming popular in image processing, especially in image segmentation. Based on the degree of the membership function, each pixel can be grouped into “natural group� of pixels according to the spatial coordinate using their values. In this work we present features extraction based on fuzzy clustering and segmentation onto the motion region for medium field surveillance application. Instead of using blob analysis, we believe that fuzzy based clustering algorithm, can also be used to generate different clusters. Incorporating the motion-based segmentation the complexity of the fuzzy clustering will also be reduced because only the motion region will be processed to the clustering algorithm.
机译:基于模糊的聚类算法在图像处理中尤其是在图像分割中正变得越来越流行。根据隶属函数的程度,每个像素可以分为“自然组”。根据像素的空间坐标使用像素值。在这项工作中,我们提出基于模糊聚类和分割到运动区域的特征提取,以用于中场监视应用。代替使用斑点分析,我们认为基于模糊的聚类算法也可以用于生成不同的聚类。结合基于运动的分割,由于仅将运动区域处理为聚类算法,因此模糊聚类的复杂度也将降低。

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