二维时空模糊熵运动检测中的自适应门限新算法  

A New Adaptive Thresholding Algorithm for Motion Detection Based on Two-Dimensional Spatio-Temporal Fuzzy Entropy Principle

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作  者:刘洋[1] 初秀琴[1] 李玉山[1] 

机构地区:[1]西安电子科技大学电路CAD研究所,陕西西安710071

出  处:《电子学报》2008年第6期1092-1097,共6页Acta Electronica Sinica

基  金:国家自然科学基金(No.60172004);陕西省自然科学基金(No.2007F05)

摘  要:提出一种基于二维时空模糊熵准则自适应确定运动检测门限的新算法.通过推导给出二维模糊熵门限的快速实现形式,利用积分和迭代操作避免了传统二维模糊熵门限求解过程中点的重复计算,将灰度级为N的图像的各种运算操作次数从O(N4)降低到小于或等于O(N3).将运动检测归结为两个二值划分问题,无需已知背景分布的具体形式和参数,利用二维模糊熵准则自适应确定门限T.实验结果表明,该方法在目标和背景对比度偏低的情况下也可以提取出完整的运动信息,易于实现实时处理.A adaptive thresholding algorithm for motion detection based on two-dimensional spatio-temporal fuzzy entropy principle is proposed. A fast solution for calculating the two-dimensional fuzzy entropy threshold is deduced, in which repeated calculation is avoided by using integral and iterative operation, and the various calculation operation is reduced from O ( N^4 ) to less than O( N^3) for N gray-level image. The motion detection is reduced to two binary partition problems, and two-dimensional spatiotemporal fuzzy entropy principle is used to determine the threshold T, where the explicit function form or parameters of background distribution are not needed to be known. The experimental results show that the information of moving objects which have low contrast to background can also be extracted completely by this method in real time.

关 键 词:二维时空模糊熵准则 运动检测门限 运动目标提取 积分操作 迭代操作 

分 类 号:TN911.73[电子电信—通信与信息系统]

 

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