基于多点对参考模型的车辆阴影消除

华南理工大学学报(自然科学版) ›› 2011, Vol. 39 ›› Issue (12): 63-69.

基于多点对参考模型的车辆阴影消除

戚其丰^1,2吴忻生^1,2邓军¹

1．华南理工大学自动化科学与工程学院，广东广州 510640; 2．华南理工大学精密电子制造装备教育部工程研究中心，广东广州 510640

收稿日期:2011-04-01 修回日期:2011-09-08 出版日期:2011-12-25 发布日期:2011-11-04
通信作者: 戚其丰(1976-) ，男，博士，讲师，主要从事数字图像处理、机器视觉等的研究． E-mail:qqifeng@ gmail.com
作者简介:戚其丰(1976-) ，男，博士，讲师，主要从事数字图像处理、机器视觉等的研究．
基金资助:
国家自然科学基金资助项目( 60835001) ;华南理工大学中央高校基本科研业务费专项资金资助项目( 2009ZM0143)

Vehicle Shadow Elimination Based on Multi-Point Pair Reference Model

Qi Qi-feng^1,2Wu Xin-sheng^1,2Deng Jun¹

1. School of Automation Science and Technology,South China University of Technology,Guangzhou 510640,Guangdong,China; 2. Engineering Research Center for Precision Electronic Manufacturing Equipment of the Ministry of Education,South China University of Technology,Guangzhou 510640,Guangdong,China

Received:2011-04-01 Revised:2011-09-08 Online:2011-12-25 Published:2011-11-04
Contact: 戚其丰(1976-) ，男，博士，讲师，主要从事数字图像处理、机器视觉等的研究． E-mail:qqifeng@ gmail.com
About author:戚其丰(1976-) ，男，博士，讲师，主要从事数字图像处理、机器视觉等的研究．
Supported by:
国家自然科学基金资助项目( 60835001) ;华南理工大学中央高校基本科研业务费专项资金资助项目( 2009ZM0143)

摘要/Abstract

摘要： 为了解决车辆检测过程中的阴影干扰问题，以点对属性为基础，利用HSL 色彩空间中前景、背景和运动阴影之间的色度、亮度属性，在给定的背景图像集中，采用离线训练的方法，于图像的全局域中建立稳定的不随环境变化的多点对参考模型．该模型充分考虑了图像全局域的颜色信息，减小了背景像素的误差，能在线消除运动阴影对车辆分割的影响，且对于复杂环境下的运动背景和光照变化具有较强的抑制作用．为减小算法的计算量，引入背景模板，减少了参与运算的像素点，提高了算法的分割效率．仿真实验表明，运用多点对参考模型消除车辆运动阴影，比其它阴影消除方法具有更强的准确性和鲁棒性．

关键词: 多点对参考模型, 阴影消除, 车辆分割, 颜色空间

Abstract:

In order to eliminate the shadow interference in a vehicle detection process,a stable multi-point pair reference model based on point pair properties,which is insensitive to the environment,is established in the global domain of the image. This model takes advantage of the hue and the luminance among the foreground,the background and the moving shadow in HSL color space and adopts the offline training method in a given background image set. By fully considering the color information of the whole image,the model reduces the error of background pixels,online
eliminates the impact of moving shadow on vehicle segmentation and strongly inhibits the moving background and illumination change in complex environments. Moreover,to simplify the computation of the proposed algorithm,background templates are introduced,which greatly reduces the number of operation pixels and improves the segmentation efficiency. Simulated results indicate that,as compared with the other vehicle shadow elimination methods,the proposed algorithm based on the multi-point pair reference model is more accurate and robust.

Key words: multi-point pair reference model, shadow elimination, vehicle segmentation, color space

戚其丰吴忻生邓军. 基于多点对参考模型的车辆阴影消除[J]. 华南理工大学学报(自然科学版), 2011, 39(12): 63-69.

Qi Qi-feng Wu Xin-sheng Deng Jun. Vehicle Shadow Elimination Based on Multi-Point Pair Reference Model[J]. Journal of South China University of Technology(Natural Science Edition), 2011, 39(12): 63-69.

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[2]	秦钟. 基于梯度方向恒定性的运动车辆阴影检测[J]. 华南理工大学学报（自然科学版）, 2008, 36(10): 43-46.