[1]韩延彬,郭晓鹏,魏延文,等.RGB和HSI颜色空间的一种改进的阴影消除算法[J].智能系统学报编辑部,2015,10(5):769-774.[doi:10.11992/tis.201410010]
HAN Yanbin,GUO Xiaopeng,WEI Yanwen,et al.An improved shadow removal algorithm based on RGB and HSI color spaces[J].CAAI Transactions on Intelligent Systems,2015,10(5):769-774.[doi:10.11992/tis.201410010]
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HAN Yanbin,GUO Xiaopeng,WEI Yanwen,et al.An improved shadow removal algorithm based on RGB and HSI color spaces[J].CAAI Transactions on Intelligent Systems,2015,10(5):769-774.[doi:10.11992/tis.201410010]
RGB和HSI颜色空间的一种改进的阴影消除算法
《智能系统学报》编辑部[ISSN 1673-4785/CN 23-1538/TP] 卷:
10
期数:
2015年第5期
页码:
769-774
栏目:
学术论文—机器感知与模式识别
出版日期:
2015-10-25
- Title:
- An improved shadow removal algorithm based on RGB and HSI color spaces
- Keywords:
- target detection; shadow removal; color space; hole phenomenon; video analysis
- 分类号:
- TP391
- 文献标志码:
- A
- 摘要:
- 在智能视频监控中,运动目标的准确提取至关重要。现有的运动目标检测算法虽然很多,但是阴影去除效果都不甚理想,因此提出了一种基于RGB和HSI颜色空间的阴影消除改进算法。该算法在分析视频中像素点被阴影覆盖和未被阴影覆盖时色调的近似一致性和亮度值成线性关系的基础上,利用2个颜色空间中组成颜色的各分量值在该颜色中所占的比例和亮度的相对变化率,实现运动目标的阴影消除。实验表明,该算法去除阴影的效果优于采用(r, g, I)颜色空间阴影去除算法,且能有效弥补运动目标孔洞的现象,是对运动目标检测算法的补充。
- Abstract:
- It is critical to exactly extract moving targets in intelligent video surveillance. There are many moving target detection algorithms, but for all the effects of shadow elimination are not ideal. In order to remove the shadow, an improved shadow removal algorithm based on RGB and HSI color spaces is presented. The analysis of the pixels in videoes shows that the hue is approximately consistent before and after the pixels are shaded, and there exists a linear relation between this approximate consistency and the value of luminance. On this basis, by utilizing the proportion of each color component in the color spaces and the relative change rates of brightness, the shadow of a moving object can be removed. The experimental results show that the shadow removal effect of this algorithm is better than that of the algorithm with (r, g, I) color space. In addition, it can also cope with holes in moving targets and is a supplement to the moving object detection algorithm.
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备注/Memo
收稿日期:2014-10-08;改回日期:。
基金项目:国家自然科学基金资助项目(61103117,61303199);山东省科技发展计划(2013YD01043);山东省高校科研计划项目(J12LN19,J14LN15).
作者简介:韩延彬,男,1979年生,副教授,中国计算机学会多值逻辑与模糊逻辑专委会委员,中国人工智能学会机器学习专业委员会通讯委员,主要研究方向为模式识别、计算智能。主持和参与国家和省部级项目多项,发表学术论文10余篇,其中被SCI、EI收录10篇;郭晓鹏,男,1992年生,硕士研究生,主要研究方向为模式识别、计算机视觉;魏延文,女,1985年生,硕士,主要研究方向为模式识别、计算机视觉;李恒建,男,1980年生,副教授,博士,中国计算机学会多值逻辑与模糊逻辑专委会委员,主要研究方向为模式识别、图像处理。主持和参与国家和省部级项目多项,发表学术论文10余篇,其中SCI、EI收录10篇。
通讯作者:韩延彬.E-mail:ise_hanyb@ujn.edu.cn.
更新日期/Last Update:
2015-11-16