MATLAB Implementation for Feature Point Extraction

This documentation presents a MATLAB program designed for multi-view feature point extraction with scale transformation resistance. Feature point extraction is crucial in computer vision as it provides foundational data for numerous applications. The program implements robust feature detection algorithms such as SIFT (Scale-Invariant Feature Transform) and SURF (Speeded-Up Robust Features) to extract distinctive keypoints invariant to scale changes. The implementation includes feature matching capabilities essential for computer vision tasks like image stitching and 3D reconstruction. Key functions involve parameter configuration for controlling feature quantity, quality threshold, and spatial distribution. Users should familiarize themselves with algorithm parameters through relevant literature before implementation to optimize performance. The code structure employs MATLAB's Computer Vision Toolbox functions like detectSURFFeatures() and matchFeatures() for efficient processing.