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复杂背景下基于图像融合的运动目标轮廓提取算法
引用本文:何卫华,李平,文玉梅,叶波.复杂背景下基于图像融合的运动目标轮廓提取算法[J].计算机应用,2006,26(1):123-0126.
作者姓名:何卫华  李平  文玉梅  叶波
作者单位:重庆大学光电工程学院,重庆,400030
摘    要:运动目标轮廓的有效提取对于目标识别、跟踪和行为的理解等后期的处理是非常重要的。受背景复杂性的影响,当背景灰度和运动目标的灰度相近时,提取的运动目标易产生空洞,某些部位无法完全恢复。根据帧差法的基本原理,提出了一种针对复杂背景的运动目标检测、轮廓提取方法。首先,对图像进行滤波处理,采用最大方差比阈值法消除了剩余部分噪声和背景,然后在三帧时间差分法基础上,利用序列中多帧图像融合运动信息,并确定参考区域,通过对原图像进行回扫描,最终提取出完整的运动目标轮廓。实验结果验证了算法的稳健性和有效性。

关 键 词:运动目标  复杂背景  帧差法  多帧图像融合  低对比度
文章编号:1001-9081(2006)01-0123-04
收稿时间:2005-07-28
修稿时间:2005-07-282005-10-08

Algorithm of extracting moving object silhouette based on frame fusion under complex background
HE Wei-hua,LI Ping,WEN Yu-mei,YE Bo.Algorithm of extracting moving object silhouette based on frame fusion under complex background[J].journal of Computer Applications,2006,26(1):123-0126.
Authors:HE Wei-hua  LI Ping  WEN Yu-mei  YE Bo
Affiliation:College of Optoelectronic Engineering, Chongqing University, Chongqing 400030, China
Abstract:Effective extraction of the moving object silhouette is essential for the subsequent processing, including target identification, tracking, behavior comprehension, and so on, In some cases, especially when there is low contrast in gray between the background and moving object, the recovered-object is often made up of holes and distorted parts. To improve the performance of extraction in such situation, a modified method based on the principle of frames subtraction was presented. Firstly pre-filtering was needed to alleviate the Gauss noise. Secondly, a maximum variance ratio threshold value was used to remove the remaining noise and background. Then some frames were fused to obtain more information about the moving object, and an area for reference was defined at the same time. After scanning the original image, the moving object silhouette was recovered. Experiment results prove that the modified method is more robust, and superior to other traditional ones.
Keywords:moving object  complicated background  frame subtraction  frames fusion  low-contrast
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