Improvement of Feature Point Algorithm Based on ORB
WANG Xinyu
LI Yuefeng
ZOU Jun
Abstract：The feature point algorithm plays an important role in image processing.The ORB(Oriented FAST and Rotated BRIEF)feature point extraction algorithm is widely used because of its rotation invariance and fast computation speed.The tradition-al ORB feature point algorithm can not detect feature points easily in light-transformed scenes,and the running time is not enough for a strong real-time system.Based on the principle of ORB feature point algorithm,this paper improves the original ORB algo-rithm by using methods such as reducing the area of detection area,optimizing the detection process,optimizing trigonometric func-tion solution,dynamic gray threshold,etc.It improves the speed of ORB feature point detection algorithm and improves the applica-bility of ORB feature point detection algorithm under different lighting conditions.Finally,experiments show that the improved ORB algorithm takes less time on average than the algorithm in OpenCV library,and can extract more feature points in scenes with vary-ing brightness.The improved algorithm is more suitable for real-time systems such as visual SLAM(Simultaneous Localization and Mapping)and systems that use ambient light to easily transform.
Keywords：characteristic pointsORBlight-transformeddynamic gray threshold
Publication Date：2025-12-20
Online Publishing Date：2026-03-09(First online date of this platform, not the publication date of the document)
Pages：6( 3347-3351,3377 )