MATLAB Implementation of SURF Feature Matching

This MATLAB program implements SURF (Speeded-Up Robust Features) feature matching for images. The package includes working examples and test images to help users understand the implementation. The program utilizes MATLAB's Computer Vision System Toolbox functions, primarily employing the detectSURFFeatures() function to identify keypoints and extract feature vectors, followed by the matchFeatures() function to establish correspondences between images using nearest-neighbor search algorithms. Users should have fundamental knowledge of SURF feature matching principles and MATLAB's computer vision capabilities before using this program. For optimal utilization, beginners are recommended to study related concepts first. The code can be further modified and optimized by adjusting parameters like 'MetricThreshold' for matching sensitivity, 'NumOctaves' for scale-space analysis, or by adding custom functionalities such as RANSAC-based geometric verification to handle various application scenarios. This implementation serves as a practical foundation for mastering SURF feature matching techniques and MATLAB programming in computer vision applications.