节点文献
一种基于统计模型的前景阴影消除算法
Shadow Elimination Algorithm for Foreground Based on Statistical Model
【摘要】 视频图像中存在的阴影是影响运动目标检测效果的关键因素之一,对阴影进行检测和消除已成为运动检测中的重要研究内容.针对阴影消除问题,本文采用直方图统计方法,将阴影特征引入到传统混合高斯模型中,基于统计特征建立阴影高斯模型;在模型基础上,提出一种新的前景阴影消除算法,将前景像素与阴影模型进行匹配,实现阴影的判定和消除.与同类算法的对比分析表明:本文算法对于不同场景下的阴影消除是准确且实时的,在阴影检测率和阴影区分度上均有显著提升.
【Abstract】 The existence of the shadow is one of the key factors which impact the result of the object detection,detecting and eliminating the shadow become the important research area in the target detection.Aiming to the shadow problem during the object detection,we used the histogram to statistic and analysis the color feature of the shadow under the HSV color space,got the shadow feature of the H,S,V channels.Then established the Gaussian shadow model on each channel according to the statistic information.Based on the model had built,we proposed a novel algorithm to eliminate the shadow,using the foreground pixels to matche the model then determine and eliminate the shadow.Compared with the similar algorithms,the results show that the proposed algorithm can eliminate the shadow correctly in real-time under different scenarios,and it performs better on the metrics of shadow detection rate and the shadow discrimination rate.
【Key words】 moving object detection; statistical feature; gaussian model; foreground; shadow eliminate;
- 【文献出处】 小型微型计算机系统 ,Journal of Chinese Computer Systems , 编辑部邮箱 ,2013年02期
- 【分类号】TP391.41
- 【被引频次】13
- 【下载频次】267