Image Processing - Feature Matching

This project aims to explore the use of feature-matching techniques in image processing and computer vision using the SIFT (Scale-Invariant Feature Transform) detector and descriptor. The project also makes use of the RANSAC (Random Sample Consensus) algorithm for removing outliers and making the dataset more robust. Moreover, a homography matrix is created from 4-point correspondence that goes through multiple iterations to transform the template image and draw a box boundary for the template image matching the target image.