测绘科学技术学报2017，Vol.34Issue(5)：475-480,6.DOI:10.3969/j.issn.1673-6338.2017.05.008
一种基于Harris-Laplace算法的亚像素角点检测方法
A Sub-Pixel Corner Detection Method Based on Harris-Laplace Algorithm
摘要
Abstract
In order to solve the problem of the drifting of pixel position and the pixel precision of Harris-Laplace detection algorithm,a sub-pixel corner detection method based on Harris-Laplace algorithm is proposed.Firstly,the multi-scale space is generated by Guassian convolution with the original image,the Harris-Laplace corners are extracted both in the original image and multi-scale images.Then,the corners clusters are acquired by projection from scale space images to the original image,and the comers in clusters are sifted by the response value of the multi-scale space corners.Finally,the exact coordinates of corners are calculated by the coordinate-weighted average.Experimental results indicate that the proposed method can provide scale invariant sub-pixel corner points with the anti-noise stability.关键词
角点检测/多尺度空间/角点集群/角点响应值/亚像素精度Key words
comers detection/multi-scale space/corners clusters/corners response value/sub-pixel precision分类
天文与地球科学引用本文复制引用
高翔,万成浩,李润生..一种基于Harris-Laplace算法的亚像素角点检测方法[J].测绘科学技术学报,2017,34(5):475-480,6.
