CAJ | 학술논문

为提高夜间环境下车辆检测的精度，提出一种基于亮度累加直方图的车辆检测算法，利用汽车尾灯的高亮特征检测自车前方车辆。通过统计大量的尾灯亮度雷息得到分割阈值，由该阈值确定最大类间方差法的初始阈值。在亮度累加直方图中采用改进的最大类间方差法确定最佳分割阈值，并使用该阈值分割图陣提取尾灯目标。结合尾灯的需状、位置和颜色等特征进霂尾灯筛选和配对，以检测到的尾灯对为目标实现夜间车辆的检测。实验结果表明，该算法能够准确地分割出尾灯目标，对夜间前方车辆的检测率较高、适应霆较好。
위제고야간배경하차량검측적정도，제출일충기우량도루가직방도적차량검측산법，이용기차미등적고량특정검측자차전방차량。통과통계대량적미등량도뢰식득도분할역치，유해역치학정최대류간방차법적초시역치。재량도루가직방도중채용개진적최대류간방차법학정최가분할역치，병사용해역치분할도진제취미등목표。결합미등적수상、위치화안색등특정진목미등사선화배대，이검측도적미등대위목표실현야간차량적검측。실험결과표명，해산법능구준학지분할출미등목표，대야간전방차량적검측솔교고、괄응정교호。
In order to improve the vehicle detection accuracy in the nighttime environment, a vehicle detection algorithm based on brightness cumulative histogram is proposed, which detects from the front vehicles via the highlight feature of the taillights. The initial threshold of Otsu method is obtained from a number of taillights statistical information. The bright objects are extracted from images, based on the improved Otsu method in brightness cumulative histogram. The characteristics such as the shape, position and color of taillights are combined to select and pair them. The front vehicles can be detected by the paired taillights. Experimental results demonstrate the accuracy of the proposed approach on taillights segmentation, and demonstrate the effectiveness and robustness of the approach on vehicle detection at night.