福建农林大学学报（自然科学版）Issue(1)：116-120,5.DOI:10.13323/j.cnki.j.fafu(nat.sci.).2016.01.020
基于马尔可夫随机场的运动物体检测方法
Detection method based on Markov random field for moving object
摘要
Abstract
Implementation of smart surveillance is an effective way to avoid potential hazard within substation. In order to more accu-rately determine the state of substation staff, which was a motion object in this case, a novel detection method based on Gauss mix-ture model and Markov random field motion was proposed. First of all, the hue, saturation, value ( HSV) color space of the images were preliminarily extracted by Gauss mixture background modeling. Then a segmentation approach based on Markov random field motion was applied to re-extract the HSV image, which was followed by shadow elimination referring to respective motion templates. Experimental results comfirmed that the proposed method was capable of precisely detecting the state of moving objects within substa-tion in different background, which laid a sound foundation for behavior analysis of motion object and image stitching.关键词
视频图像/高斯混合模型/运动检测/马尔可夫随机场Key words
video image/Gauss mixture model/motion detection/Markov random field分类
信息技术与安全科学引用本文复制引用
魏丽芳,林甲祥,杨长才,董恒,周术诚..基于马尔可夫随机场的运动物体检测方法[J].福建农林大学学报（自然科学版）,2016,(1):116-120,5.基金项目
国家自然科学基金资助项目(41401458)；福建省自然科学基金资助项目(2014J05045) （41401458）
