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July1

## Optimal-RANSAC

Matlab

My main pages
Acknowledgement:Our Optimal-RANSAC was developed from the code by Peter Kovesi and is made publicly available with his consent.
The usage is explained in each file. The code has been updated recently!

## Description

Optimal-RANSAC finds the optimal set in almost every run and will therefore be repeatable as it yelds the same result. However it has some limitations. It works robustly for images with one plane only (hence only one model), e.g. for aerial images. It will yield the same result at least 99.95% of the times calledfor set with more than about 30 inliers. This number can be increased even further by demanding more equal results. Please see the last parameter ner (Number of Equal iteRations). If there are fewer inliers the parameter ner must be increased. When dealing with images taken on the ground of houses and similar it will sometimes yield different sets, all optimal with regard to the model it happens to find. Generally we have found that acc=1/(2 min(size(image)), and t=acc*8, produced reliable results.
One major advantage with the code is that it is able to cope with very low inlier ratios, even below 5%! It will be much faster than the theoretical speed fur such sets. Nonetheless, it will be a bit slower for high inlier ratio sets, but it will still yield the optimal set in every run.

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August28

## Log Polar Transform using Gaussian Filtering

Matlab

My main pages
Acknowledgement:
The usage is explained in each file.

## Description

The Log Polar TRansform (LPT) is not always implemented in a correct way. This implementation is based on Gaussian Sampling.

## Matlab Code

• logpolarGauss.m
• Log Polar Transformation.
• Sample2D.m
• 2D Sampling using Gaussian Filtering.
• Gauss2D.m
• A 2D Gaussian Function.

### Example code:

An example of how to use Sample2D.m
This code rotates a part (depending on the chosen center and radius) of an image, using Sample2D. The size of the output image can als be set, as well as the sigma and mask size for the Gaussian filtering.
• imrotGauss.m
• Rotates a part of an image using Gaussian Filtering.

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July1

## Kernel for Image Derivatives

Matlab

My main pages
Acknowledgement:
The usage is explained in each file.

## Description

Efficient first and second order derivatives were proposed in Simple filter design for first and second order derivatives by a double filtering approach.

## Matlab Code

• Kernel.m
• Different Kernels for Image derivatives

### Example code:

[k, d, d2] = kernel('Cubic');
Iu=-conv2(conv(d,k),conv(k,k),im,'same');
Iv=-conv2(conv(k,k),conv(d,k),im,'same');

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July1

## Mean-Max-Min Features

Matlab

My main pages
Acknowledgement:
The usage is explained in each file.