SIFT-on-MATLAB

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This is an Implementation of "SIFT Features" on MatLab.

SIFT-on-MATLAB 최신버젼 다운로드

최종 버전 다운로드 (.zip)

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# SIFT-on-MATLAB
An implementation of [Distinctive image features from scale-invariant keypoints](https://scholar.google.com/citations?view_op=view_citation&hl=en&user=8vs5HGYAAAAJ&citation_for_view=8vs5HGYAAAAJ:u_35RYKgDlwC), created by [David Lowe](https://scholar.google.com/citations?user=8vs5HGYAAAAJ). This is a term project for "Advanced Topics in Medical Image Analysis" course at Middle East Technical University.
# Usage
Read an image in MatLab and convert it into gray scale image then use it as input for `SIFT` function.
- `SIFT(Image, Octaves, Scales, Sigma):` Main function takes **gray scale image**, **number of octaves**, **number of scales per octaves** and **initial value for sigma**. Returns key points inside a cell array.

Example:
```
image = imread('image.jpg');
image = double(rgb2gray(image));
keyPoints = SIFT(image,3,5,1.6);
```
Key points created in the process are objects. All of the key points are returned in a cell array. Each key point contains:
- `coordinates():`returns **[x, y]** coordinate of the key point on image.
- `direction():`Returns general Direction of the key point.
- `magnitude():`Returns the magnitude of general direction vector.
- `octave():`Returns number of the octave which the key point extracted from.
- `scale():` Returns sigma value which the image is convolved with.
- `descriptor():`Returns a vector containing the descriptor.
# Image Visualizer
This function's main purpose is to illustrate the keypoints on the image. The function `SIFTKeypointVisualizer` will be called after extracting keypoints.

Example:
```
image = SIFTKeypointVisualizer(image,keyPoints);
imshow(uint8(image));
```
# Dependencies
This code is dependent on some functions within `Image Processing Toolbox` version `9.2`.

This code should be compatible with any MatLab newer than `R2015a`.

# Disclaimer
All the rights to **"Distinctive image features from scale-invariant keypoints"** are reserved for **[University of British Columbia](http://www.cs.ubc.ca/~lowe/keypoints/)**. *A license must be obtained from the University of British Columbia for any commercial applications.*

## 2023-09-09 Update to the Disclaimer

[The patent](https://patents.google.com/patent/US6711293B1/en) is expired on **March 6, 2020**, and the algorithm is now - *possibly* - public knowledge.

# Contact
For further information please contact [zabardast.amin@metu.edu.tr](mailto:zabardast.amin@metu.edu.tr) or [kilic.ozkan@metu.edu.tr](mailto:kilic.ozkan@metu.edu.tr).

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