An Improved ORB Feature Extraction Algorithm. (August 2020)

• Record Type: Journal Article
• Authors: Geng, Chuanping; Yang, Junjie; Lin, Jinchen; Yu, Ting; Shi, Kexin
• Is Part Of: Journal of physics. Volume 1616(2020)
• Publication Date: 2020-08
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1616/1/012026
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: In this paper, an improved ORB feature extraction algorithm is proposed to solve the insufficient detection effect of the traditional ORB algorithm on the image edges as well as the low actual extraction of feature points. First, the image pyramid layering was established, and then on basis of the improved oFAST12-20 corner point algorithm, the method with a setting dynamic threshold, according to the idea of adaptive threshold, was proposed to extract feature points, and the candidate set of feature points was obtained. Then, Harris algorithm was used to calculate the response value of each candidate point, and the response value was sorted from high to low. Finally, the top 80% of the feature points with high response value were extracted as the most important feature points. The experimental results show that the improved oFAST algorithm improved the extraction rate of feature points and reduces the algorithm time compared with the traditional ORB corner detection.