CAJ | 학술논문

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YCbCr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。
제출료일충기우구역협방차적차위상태감측식별방법。차위상태감측식별적난점재우광선적변화、음영、이급배경적간우，통과제취YCbCr색채공간적량도Y분량，용Sobel산자획득각개상소점수평근수직방향적적량도제도，진이구건특정향량，연후용구역협방차구진래묘술차위소재적구역，최후용협방차구진적거리측도특성주출차위상태(공한/점령)판결，여이전적방법비교구유일차채집실현다차위식별적돌출우점，차해방법대광선불명감，로봉성교강。
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.