An Image Matching Method Based on SIFT Feature Extraction and FLANN Search Algorithm Improvement
Shigang Wang, Zhenjin Guo, Yang Liu
Abstract
In order to solve the problems of less feature information and high mismatching rate in traditional image matching algorithms, this paper proposed to extract and describe features based on the SIFT algorithm. FLANN algorithm was used to pre-match feature points, and RANSAC algorithm was used to optimize the matching results, so as to realize real-time image matching and recognition. Experimental results show that the proposed algorithm has better accuracy and better matching effect than traditional image matching methods.
Topics & Concepts
RANSACScale-invariant feature transformMatching (statistics)Artificial intelligenceComputer sciencePattern recognition (psychology)Feature (linguistics)Image (mathematics)Blossom algorithmFeature extractionComputer visionImage matchingFeature matchingAlgorithmMathematicsPhilosophyLinguisticsStatisticsAdvanced Image and Video Retrieval TechniquesRobotics and Sensor-Based LocalizationRobotic Path Planning Algorithms