面向复杂背景中彩色立体图像的障碍物检测

目标识别技术作为图像理解领域的核心研究内容之一,一直以来是文献中讨论的热门话题.随着计算机科学的发展以及彩色成像设备的普及,越来越多的彩色立体图像在实际生产、生活中得到应用,面向彩色立体图像的目标识别技术逐渐成为吸引学者注意力的新方向.本文基于立体视觉信息,对安装在行进车辆上的两个摄像机在一段时间内获取的立体视频信息进行分析,提取车辆前方可能对行车安全造成威胁的障碍物.在V视差理论的基础上引入两个改进算法首先对原始立体图像进行数据净化和前景/背景分割,使后续算法不受复杂、多变背景的干扰,同时减少数据处理的冗余.然后使用绝对值差(SAD)[9]法直接计算彩色立体图像的浓密视差图,而无需彩色到灰度图像的转换.实验证明,本文提出的改进算法针对实际立体图像可以准确、快速地提取障碍物信息.

Color Stereo Image-Based Obstacle Detection with Complicated Backgrounds

This paper deals with stereo sequences obtained from two parallel video cameras mounted on a moving vehicle and aims to extract all potentially dangerous obstacles. Based on the V-disparity theory, an improved algorithm is proposed to eliminate the negative effect caused by the complicated changing background and reduce the data quantity. It then directly calculates the dense disparity map from color stereo image pairs without the color to greylevel transformation. Experiments show that the proposed improvement can achieve high accuracy and fast speed in obstacle extraction in color stereo images.