西安电子科技大学电路CAD研究所,陕西,西安,710071
纸质出版:2008
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刘 洋, 初秀琴, 李玉山. 二维时空模糊熵运动检测中的自适应门限新算法[J]. 电子学报, 2008,36(6):1092-1097.
LIU Yang, CHU Xiu-qin, LI Yu-shan. A New Adaptive Thresholding Algorithm for Motion Detection Based on Two-Dimensional Spatio-Temporal Fuzzy Entropy Principle[J]. Acta Electronica Sinica, 2008, 36(6): 1092-1097.
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(N
4
)降低到小于或等于O(N
3
)
.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 algotithm 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 spatio-temporal 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 m
oving objects which have low contrast to background can also be extracted completely by this method in real time.
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