计算机应用与软件2012，Vol.29Issue(5)：254-255,300,3.
基于简化Forstner算子改进的SIFT无人机图像识别算法
IMPROVED SIFT IDENTIFICATION ALGORITHM FOR UAV IMAGE BASED ON SIMPLIFIED FORSTNER OPERATOR
息朝健 1郭三学1
作者信息
- 1. 武警工程学院装备运输系 陕西 西安 710086
- 折叠
摘要
Abstract
This paper addresses the seeking of an identification algorithm for image target fitting UAV features to increase the efficiency of image identification according to the characteristics of UAV that the image information captured is huge and the real-time processing requirement is high. SIFT algorithm has good accuracy and robustness and can overcome some effect of image deformation and occlusion, but it is still hard to achieve real-time processing of UAV images. In the paper we use simplified Foretner operator to improve SIFT algorithm, reduce the computation of feature point recognition process in it. Through the simulation experiment, it proves that the improved SIFT algorithm can raise the accuracy and matching speed of the identification, meet the requirements of UAV in its target identification precision and speed in complicated background.关键词
目标识别/SIFT算法/Forstner算子/DOG空间Key words
Target identification/ SIFT/ Forstner operator/ Difference of Gaussian SCALE - space分类
计算机与自动化引用本文复制引用
息朝健,郭三学..基于简化Forstner算子改进的SIFT无人机图像识别算法[J].计算机应用与软件,2012,29(5):254-255,300,3.
