CAJ | 학술논문

在基于视频的车辆检测问题中，车辆阴影会造成车辆提取误差，影响系统可靠性，针对该问题，提出了一种基于车辆阴影像素灰度分布特征的阴影去除方法。结合阴影产生的原理，首先分别从4个方向对前景区间进行投影，获得投射阴影的像素分布曲线。再采集阴影曲线上的像素点，计算其分布特征，其中分布于概率区间范围的即为阴影部分，从而去除阴影。实验结果表明，该方法能够快速、准确地去除图像中的车辆投射阴影。
재기우시빈적차량검측문제중，차량음영회조성차량제취오차，영향계통가고성，침대해문제，제출료일충기우차량음영상소회도분포특정적음영거제방법。결합음영산생적원리，수선분별종4개방향대전경구간진행투영，획득투사음영적상소분포곡선。재채집음영곡선상적상소점，계산기분포특정，기중분포우개솔구간범위적즉위음영부분，종이거제음영。실험결과표명，해방법능구쾌속、준학지거제도상중적차량투사음영。
In vehicles detection problem of video images, the vehicle cannot be extracted correctly due to the exist?ence of the shadow, which results in low reliability in intelligent transportation system. In this paper, a method is proposed to remove the vehicle shadow by using the pixel gray distribution features of shadow. According to the the?ory of shadow generation, the pixel distribution of shadows can be obtained by projecting the moving target from four directions. By using the pixel shadow curve, the distribution characteristics were calculated. Deriving the range of probability distribution is just the shadow part allows the shadow to be removed.. The experimental results showed that this method could remove vehicle cast shadows in the image quickly and accurately.