航空兵器Issue(5)：32-35,4.
基于机器视觉的无人机红外合作目标分割方法研究
Research on Segmentation of UAV＇s IR Cooperative Target Based on Machine Vision
摘要
Abstract
In the problem of cooperative target segmentation for the landing of unmanned aerial vehicle （UAV）, the segmentation results of the double Otsu algorithm and maximum entropy algorithm are unsatisfactory when the target accounts for the image less than 0.2%. In order to promote the effects, an adaptive region growing method is proposed. Firstly, the pixel number of the cooperative target is set through the estimated distance between airborne camera and the landing target. Secondly, N brightest points of the image are found out automatically utilizing the characteristics of IR images. Then, the geo- metric center of the N brightest points is set to be the seed point. Finally, the terminal principle is determined by the statistical properties of histogram. The experimental results show that this method is better than the common segmentation methods, such as double Otsu and maximum entropy method.关键词
红外图像/Otsu算法/最大熵算法/自适应区域生长法/红外分割Key words
infrared image/Otsu algorithm/maximum entropy algorithm/adaptive region growingmethod/IR segmentation分类
航空航天引用本文复制引用
汪凌艳,徐贵力,王彪,陈欣,田裕鹏,叶永强..基于机器视觉的无人机红外合作目标分割方法研究[J].航空兵器,2011,(5):32-35,4.基金项目
基金项目：国家自然科学基金项目 （）
航空基金项目 （）
