一种基于图像处理的目标识别算法

摘要

The mobile robot Simultaneous Localization and Mapping ( SLAM) in unknown environments has been considered to be an important issue in mobile robotics research domain. As autonomous robots, possessing visual acquisition capability is very crucial to explore unknown environments reliably, SIFT ( Scale Invariant Feature Transform) key points are powerful in detecting objects under various imaging conditions. This paper presents an algorithm to optimize the SIFT vector size, complexity and matching time Experimental results demonstrate the effectiveness of the proposed algorithm.%在未知环境中,移动机器人的同步定位与地图创建是机器人研究领域的一个非常重要的问题.作为自主机器人,能够可靠地探索未知环境中的目标或局部环境,是否具有视觉信息采集能力是非常重要的,基于尺度不变的特征变换算法(SIFT)在图像匹配与检测方面具有强大的功能.提出了一种方法来优化SIFT特征向量的维度,降低算法的复杂度,提高算法的在线实时去处速度,实验结果证明了该算法的有效性.