北京航空航天大学学报 ›› 2020, Vol. 46 ›› Issue (9): 1763-1769.doi: 10.13700/j.bh.1001-5965.2020.0054

• 论文 • 上一篇    下一篇

一种基于区域划分的改进ORB算法

孙浩, 王朋   

  1. 山东交通学院 信息科学与电气工程学院, 济南 250357
  • 收稿日期:2020-02-27 发布日期:2020-09-22
  • 通讯作者: 王朋 E-mail:knightwp@126.com
  • 作者简介:孙浩 男,硕士研究生。主要研究方向:图像特征提取与匹配;王朋 男,博士,副教授,硕士生导师。主要研究方向:数字图像处理、视频编码与传输控制、计算机视觉。
  • 基金资助:
    国家自然科学基金(61502277);山东省自然科学基金(ZR2015FL018)

An improved ORB algorithm based on region division

SUN Hao, WANG Peng   

  1. School of Information Science and Electrical Engineering, Shandong Jiao Tong University, Jinan 250357, China
  • Received:2020-02-27 Published:2020-09-22
  • Supported by:
    National Natural Science Foundation of China (61502277); Natural Science Foundation of Shandong Province (ZR2015FL018)

摘要: 针对传统ORB算法所提取的特征点分布不均匀、存在冗杂,且不具有尺度不变性的问题,提出了一种基于区域划分的改进ORB算法。算法根据需要提取的特征点总数和所划分的区域个数计算每个小区域需要提取的特征点个数,解决了在特征点提取过程中特征点重叠和特征点冗余的问题;通过构建图像金字塔,在每一层图像金字塔上提取特征点,解决了ORB算法提取的特征点不具有尺度不变性的问题。实验结果表明:在不损失图像匹配精度的同时,所提算法提取的特征点更加均匀合理,在提取速度上也较传统ORB算法提升了16%左右。

关键词: ORB算法, 特征点提取, 区域划分, 图像金字塔, 图像匹配

Abstract: The feature points extracted by the traditional ORB algorithm are not evenly distributed, are redundant and have no scale invariance. To solve this problem, this paper proposes an improved ORB algorithm based on region division. According to the total number of feature points to be extracted and the number of regions to be divided, the algorithm calculates the number of feature points to be extracted for each region, which solves the problem of feature point overlap and redundancy in the feature point extraction process. By constructing the image pyramid and extracting feature points on each layer, the problem that the feature points extracted by ORB algorithm do not have scale invariance is solved. The experimental results show that the feature points extracted by our algorithm are more uniform and reasonable without losing the accuracy of image matching, and the extraction speed is about 16% faster than that of the traditional ORB algorithm.

Key words: ORB algorithm, feature point extraction, region division, image pyramid, image matching

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