Shadow Removal for Background Subtraction Using Illumination Invariant Measures

被引：1
|
作者：
Lee, Chulhee [1 ]
Lee, Sangwook [1 ]
Ok, Jiheon [1 ]
Lee, Jaeho [1 ]
机构：
[1] Yonsei Univ, Dept Elect & Elect Engn, Seoul 120749, South Korea
来源：
FOURTH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS, MODELLING AND SIMULATION (ISMS 2013) | 2013年
关键词：
shadow removal; background subtraction;
D O I：
10.1109/ISMS.2013.33
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we propose methods for shadow removal in static background environment. Accurate background subtraction is essential to detect and track various objects. Shadow and objects similar in color are major problems in background subtraction and tracking. In order to address these problems, we propose shadow removal method for background subtraction using illumination invariant measures. First, we computed a reference background image and the illumination invariant measures were applied to the reference background image and an input image. We compared the proposed method with some existing background subtraction methods. The experimental results showed that the proposed method produced more accurate results.
引用
收藏
页码：237 / 239
页数：3
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