基于朗斯基函数的混合高斯模型运动目标检测  

New method for mixture Gaussian background model and moving object detection based on Wronskian function

作　　者：王宝珠[1] 胡洋[1] 郭志涛[1] 刘翠响[1] Wang Baozhu Hu Yang Guo Zhitao Liu Cuixiang(School of Electronic ＆ Information Engineering, Hebei University of Technology, Tianjin 300401, China)

机构地区：[1]河北工业大学电子信息工程学院,天津300401

出　　处：《计算机应用研究》2016年第12期3880-3883,共4页Application Research of Computers

基　　金：河北省高等学校科学技术研究青年基金资助项目(Q2012012)

摘　　要：针对传统的混合高斯模型在进行运动目标检测时存在拖影和性能差的缺点,提出了一种融合朗斯基函数和帧间差分法的混合高斯背景建模算法。该改进算法通过朗斯基矩阵行列式判断相邻像素间空间域相关性,以此增加模型参数更新条件,改进模型参数更新机制;并利用帧间差分法检测运动目标轮廓的灵敏性,将两种检测结果布尔或运算,完善目标轮廓。实验结果表明,该改进算法对拖影现象达到很好的抑制作用,并使算法检测性能得到提高。Considering the shortcomings, e. g. , trailing smear and lower performance, of the traditional GMM in the process of moving object detection, this paper proposed an improved Gaussian mixture model algorithm fusing Wronskian function and frames difference method. After the process of Gaussian mixture model,it judged the spatial domain correlation between neighboring pixels by the value of the Wronskian matrix determinant which increased the update condition of the model parameters and improved the updating mechanism of the model parameters. Finally, using the sensitivity of frames difference method to detect moving target contour,it applied Boolean OR operation on the results of improved GMM and frames difference method to get the preferable moving object. The experimental results show that the improved algorithm can effectively suppress the phenomenon of the trailing smear and enhance the detection performance.

关 键 词：混合高斯模型 运动目标检测 朗斯基函数 帧间差分法 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]