海南热带海洋学院学报2024，Vol.31Issue(2)：47-52,6.DOI:10.13307/j.issn.2096-3122.2024.02.07
基于改进ORB特征的图像处理方法
Image Processing Method Based on Improved ORB Features
摘要
Abstract
As for the traditional ORB(Oriented Fast and Rotated Brief)algorithm,it is sometimes difficult to meet the actual requirements of certain applications in terms of computing speed and accuracy.In the feature point extraction stage,the pyramid optical flow method is used to extract feature points and divide the effective and ineffective regions into fea-ture points,so as to reduce the number of feature point matches and improve the speed of feature point matching for the subsequent operations.In the feature point matching stage,the Euclidean distance in the traditional algorithm is changed to Manhattan distance,and finally the MLESAC algorithm is used to eliminate the false matching points.The SURF(Speeded up robust features)algorithm,SIFT(Scale-invariant feature transform)algorithm,ORB algorithm and the improved ORB algo-rithm are used to process two images with different lighting conditions,blurring degrees and scale sizes.The improved ORB algorithm is superior to the traditional ORB algorithm both in terms of matching speed and matching accuracy.关键词
信息熵/曼哈顿距离/最大似然共识Key words
information entropy/Manhattan distance/maximum likelihood consensus分类
信息技术与安全科学引用本文复制引用
郭俊阳,胡德勇,潘祥,田德红,王伟..基于改进ORB特征的图像处理方法[J].海南热带海洋学院学报,2024,31(2):47-52,6.基金项目
安徽省重点研究和开发计划(面上攻关)项目(2021zygzts029) （面上攻关）
芜湖市科技计划(重点研发)项目(2021yf28) （重点研发）
