基于视觉的无人机着陆时机场标记的检测与识别  

Airport Runway Marking Detection and Identification of Unmanned Landing Vehicle Based on Vision

作　　者：王洪群[1] 彭嘉雄[1] 李玲玲[1] 

机构地区：[1]华中科技大学模式识别与人工智能研究所

出　　处：《模式识别与人工智能》2006年第6期764-770,共7页Pattern Recognition and Artificial Intelligence

基　　金：国家自然科学基金资助项目(No.10477007)

摘　　要：主要研究基于视觉的无人机在自主着陆时,机场跑道在图像中的检测和识别问题。首先,提取一些高亮度斑点,然后采用特殊聚类处理算法对这些含背景噪声、伪目标的点进行聚类,并根据透视原理、矩形约束条件以及目标的前视约束条件共同建立识别模型。在这些聚类中使用识别模型进行识别,这在很大程度上减少计算时间,实验表明,在距离跑道较远、跑道标记不很清晰的情况下,仍然可以有效检测和识别跑道,适合于基于视觉的无人机的自主着陆过程。In this paper, the proplem how to detect and recognize the airport runway marking in images is discussed. These images are obtained by a landing unmanned air vehicle （UAV） based on vision. Some spots of high light are extracted and grouped into several small clusters using a special clustering algorithm. An identification model is constructed using the perspective model, the rectangular fiat-plate constraint and the prior views of the scene constraint conditions. Then the runway spots in these clusters using this identification model can be datected. The computational time is greatly cut down by this classification process. The experimental results show that the proposed algorithm is very suited to the landing of UAV.

关 键 词：机场标记 检测与识别 无人机(UAV) 自主着陆 图像处理 

分 类 号：V279[航空宇航科学与技术—飞行器设计]