改进的边缘高斯混合模型运动目标检测  

Moving Object Detection Based on Improved Edge Gaussian Mixture Models

作　　者：沈婷婷[1] 仲思东[1,2] 鄢文浩 

机构地区：[1]武汉大学电子信息学院,武汉430079 [2]测绘遥感信息工程国家重点实验室,武汉430079

出　　处：《电光与控制》2017年第4期43-45,70,共4页Electronics Optics & Control

基　　金：国家"九七三"计划资助项目(2012CB725301);测绘地理公益性行业科研专项项目(201412015)

摘　　要：为解决高斯混合模型中噪声和光照变化带来的影响以及运算量大等问题,先通过帧差法确定运动目标大致区域,筛选后在确定区域内采用混合高斯模型重建背景,并运用SUSAN算子进行边缘检测,形态学处理后将两者结果进行"与"运算;区域外部分按照当前帧背景更新,两部分综合得到最终的运动目标。实验结果显示,改进算法有良好的鲁棒性,能很好地适应光照变化,检测结果高效准确,可以应用于目标跟踪领域。Gaussian mixture model has a huge computation cost, and is affected by the changes of noise and illumination. To solve the problems, frame difference method is used to roughly determine the moving target areas. After screening, Gaussian mixture model is applied in the determined area to reconstruct the background, and SUSAN operator is used to extract the edge at the same time. After morphological processing, AND operation is implemented to the results. In the meanwhile, the outside area is updated according to current frame. The moving target is obtained by integrating the two parts. Experiments show that the improved algorithm has good robustness and is well adaptive to illumination changes. With accurate and efficient detection performance, the improved algorithm can be applied to target tracking field.

关 键 词：运动目标检测 高斯混合模型 帧差法 SUSAN算子 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]