航空学报 > 2007, Vol. 28 Issue (增): 136-140

Bayesian分类方法在微小型飞行器视觉导航中的应用

周宇,黄显林,介鸣,宋卓异   

  1. 哈尔滨工业大学 控制理论与制导技术研究中心
  • 收稿日期:2006-10-25 修回日期:2007-01-30 出版日期:2007-08-10 发布日期:2007-08-10
  • 通讯作者: 周宇

Bayesian Classifier’s Application to Micro Aerial Vehicle’s Visual Navigation

ZHOU Yu,HUANG Xian-lin,JIE Ming,SONG Zhuo-yi   

  1. Center of Control Theory and Guidance Technology, Harbin Institute of Technology
  • Received:2006-10-25 Revised:2007-01-30 Online:2007-08-10 Published:2007-08-10
  • Contact: ZHOU Yu

摘要:

在微小型飞行器的视觉导航中,图像分割的基本工作是将天地两部分分割开。这是形成整个视觉导航系统闭环控制的基础。而欲实现天地分割,则以特征线的提取为前提。本文分别从自底向上和自顶向下两种思路出发,利用广义Hough变换和基于多尺度最小方差的方法,进行了全局特征线的提取。然后,采用Bayesian分类的方法,实现了对微小型飞行器视觉导航至关重要的天地分割。通过具有典型意义的仿真实验,比较了两种方法所获得的结果,揭示了两种方法应用于微小型飞行器视觉导航的优点和缺点。

关键词: Bayesian分类, 飞行器视觉导航, 广义Hough变换

Abstract:

In micro air vehicle’s visual navigation, splitting the image into two parts (sky and ground) is a fundamental problem. This is the prerequisite of the visual navigation system’s closedloop control. However, the foundation of sky-ground segmentation is the extraction of the characteristic line. By using the design philosophies of bottom-up and top-down respectively, both generalized Hough transform method and multiscale least square based line extraction method are realized in this paper.

Key words: Bayesian , classifier,  , aircraft , visual , navigation,  , generalized , Hough , transform

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