计算机与现代化Issue(6)：42-43,47,3.DOI:10.3969/j.issn.1006-2475.2013.06.012
基于前景分割的自阴影去除算法
Serf Shadow Removal Algorithm Based on Foreground Segmentation
刘振翔 1马银平1
作者信息
- 1. 南昌航空大学信息工程学院,江西南昌330063
- 折叠
摘要
Abstract
Removing identifying moving objects from a video sequence is a fundamental and critical task in many computer vision applications and a robust segmentation of motion objects from the static background is generally required.Segmented foreground objects generally include their self shadows as foreground objects since the shadow intensity differs and gradually changes from the background in a video sequence.Moreover,self shadows are vague in nature and have no clear boundaries.To eliminate such shadows from motion segmented video sequences,the paper proposes an algorithm based on inferential statistical difference in Mean (Z) method.This statistical model can deal scenes with complex and time varying illuminations without restrictions on the number of light sources and surface orientations.Results show that the algorithm can effectively and robustly detect associated self shadows from segmented frames.关键词
前景分割/自阴影/推论统计/Z检验Key words
foreground segmentation/self shadow/inferential statistics/Mean (Z) test分类
信息技术与安全科学引用本文复制引用
刘振翔,马银平..基于前景分割的自阴影去除算法[J].计算机与现代化,2013,(6):42-43,47,3.
