SIFT Algorithm (Scale-Invariant Feature Transform) - MATLAB Implementation
MATLAB program code implementation of the SIFT (Scale-Invariant Feature Transform) algorithm for feature detection and description
PCA-Enhanced Scale Invariant Feature Transform (SIFT) Algorithm
Source code implementation of PCA-integrated SIFT algorithm for robust image object detection and recognition, featuring dimensionality reduction and keypoint descriptor optimization.
MATLAB Code Implementation for Image Matching
Image matching implementation with three core components: match.m (testing program to verify matching accuracy), sift.m (core algorithm for Scale-Invariant Feature Transform), and appendimages.m (function that creates composite images showing matched pairs with connecting lines). Fully executable code.
SIFT Algorithm for Precise Image Matching and Object Detection
SIFT Algorithm for Accurate Image Matching and Object Detection with Scale-Invariant Feature Detection
Feature Matching Using SIFT Algorithm
A program implementing SIFT algorithm for feature matching, which detects keypoints and establishes correspondences between keypoints in two images. The implementation includes sample images demonstrating excellent matching results with techniques for scale-space extrema detection and descriptor generation.
Enhanced SIFT Algorithm Implementation with Harris Operator and Dimensionality Reduction
This implementation addresses limitations in standard SIFT by integrating Harris corner detection for more efficient feature point localization and reducing feature vector dimensionality while maintaining rotation and scale invariance. The approach significantly improves computational efficiency and robustness in image registration tasks.
Rapid Implementation of SIFT Algorithm
Fast implementation of SIFT algorithm for feature point extraction and matching between reference and target images, with code-level optimization insights
SIFT Algorithm MATLAB Implementation Source Code
MATLAB source code implementation of the SIFT algorithm for image feature matching applications
MATLAB Code Implementation for Image Stitching
Image stitching implementation using SIFT algorithm for feature point extraction and matching, solving homography matrix, performing affine transformation based on computed homography, and finally stitching images. The code includes comprehensive comments for easy understanding, making it suitable for developers interested in computer vision applications.
Vedaldi's MATLAB Implementation of D.G. Lowe's SIFT Algorithm
This upload contains Vedaldi's MATLAB implementation of D.G. Lowe's SIFT algorithm. Although similar source code exists online, this attached code has been specifically compiled, tested, and verified to run directly without modifications. A critical bug in sift.m has been identified and fixed (with notification sent to Mr. Vedaldi), ensuring reliable feature extraction performance.