基于区域协方差的车位识别方法  

Texture-Based Covariance Matrix for Parking Lot

作　　者：丁侨俊 蔡坚勇[1,2,3,4] 陈顺凡[1,4] 黄海涛[1] 刘华锐[1] 蔡娟[1] 

机构地区：[1]福建师范大学光电与信息工程学院,福州350007 [2]福建师范大学医学光电科学与技术教育部重点实验室,福州350007 [3]福建师范大学福建省光子技术重点实验室,福州350007 [4]福建师范大学智能光电系统工程研究中心,福州350007

出　　处：《计算机系统应用》2015年第6期148-152,共5页Computer Systems & Applications

基　　金：福建省产学科技重大项目(2013H61010023)

摘　　要：提出了一种基于区域协方差的车位状态监测识别方法.车位状态监测识别的难点在于光线的变化、阴影、以及环境的干扰,通过提取YCb Cr色彩空间的亮度Y分量,用Sobel算子获得各个像素点水平跟垂直方向的的亮度梯度,进而构建特征向量,然后用区域协方差矩阵来描述车位所在的区域,最后用协方差矩阵的距离测度特性做出车位状态(空闲/占领)判决,与以前的方法比较具有一次采集实现多车位识别的突出优点,且该方法对光线不明感,鲁棒性较强.In this paper, we proposed a method of parking space detection based on covariance matrix. The challenges of parking space detection come from luminance variation, shadow, and the interference of environment. For our solution, first of all, we extract Y-component from YCbCr color space, using Sobel operator for each pixel level with the brightness of the vertical gradient, and then construct the feature vector. Next, we use covariance matrix to describe a parking lot. Finally, we make parking state （free/occupied） with the distance of the covariance matrix measure characteristics. Compared with the previous methods, it has a great advantages of one-collection implement multiple identify parking Spaces, and a strong robustness.

关 键 词：YCb Cr色彩空间 SOBEL算子 亮度梯度 区域协方差矩阵 距离测度 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]