河北科技大学学报2017，Vol.38Issue(3)：237-243,7.DOI:10.7535/hbkd.2017yx03004
无人驾驶车辆基于角点和斑点的特征提取算法
A feature extraction algorithm based on corner and spots in self-driving vehicles
摘要
Abstract
To solve the poor real-time performance problem of the visual odometry based on embedded system with limited computing resources, an image matching method based on Harris and SIFT is proposed, namely the Harris-SIFT algorithm.On the basis of the review of SIFT algorithm, the principle of Harris-SIFT algorithm is provided.First, Harris algorithm is used to extract the corners of the image as candidate feature points, and scale invariant feature transform (SIFT) features are extracted from those candidate feature points.At last, through an example, the algorithm is simulated by Matlab, then the complexity and other performance of the algorithm are analyzed.The experimental results show that the proposed method reduces the computational complexity and improves the speed of feature extraction.Harris-SIFT algorithm can be used in the real-time vision odometer system, and will bring about a wide application of visual odometry in embedded navigation system.关键词
车辆工程/无人驾驶车辆/特征提取/SIFT/Harris/RANSACKey words
vehicle engineering/self-driving vehicles/feature extraction/SIFT/Harris/RANSAC分类
信息技术与安全科学引用本文复制引用
冯玉朋,曾庆喜,马杉,方啸..无人驾驶车辆基于角点和斑点的特征提取算法[J].河北科技大学学报,2017,38(3):237-243,7.基金项目
国家自然科学基金(51505221) （51505221）
中国博士后科学基金(YBA16027) （YBA16027）
国家重点实验室开放基金 （）
南京航空航天大学研究生创新基地(实验室)开放基金(kfjj20160216) （实验室）
