**HARRIS_CORNER_CVIP**

**harris_corner_cvip()** - a spatial-domain method for corner detection.

## Contents

## SYNTAX

[ CRF ] = harris_corner_cvip( input_img , threshold, std, alfa, maxsupress)

Input Parameters include:

- input_img - The input image. Can be multiband

- threshold - A rational value in the interval [0,1]. It is used in the thresholding step as a coefficeient multiplied to the maximum gray level in the input image.

- std - The Standard Deviation of the Gaussian blur kernel. the size of the gaussian is related to std by: size = 4*std Thus we have 2 standard deviation of the gaussian inside the kernel.

- alfa - Sensitivity value.

- maxsupress - Option to supress non-maxima either in a neighbourhood or based on direction. It is either '1' or '2'. Default: 2.

## DESCRIPTION

This is developed by Harris ans Stephens in 1998.This method consists of four steps 1. Blur the image with 2-D Gaussian convolution mask. 2. Find the approximate brightness gradient in two perpendicular directions. 3. Blur two brightness results with 2-D Gaussian. 4. Find the corner response function(CRF). 5. Threshold the CRF and apply non maxima supression.

## REFERENCE

1.Scott E Umbaugh. DIGITAL IMAGE PROCESSING AND ANALYSIS: Applications with MATLAB and CVIPtools, 3rd Edition.

## EXAMPLE

% original image I = imread('Shapes.bmp'); % threshold value from [0,1] threshold = .01; % standard deviation std = 4; % alfa alfa = 0.5; %Option to supress non-maxima either in a neighbourhood or based on direction. maxsupress = 2; % resultant Corner response [ CRF ] = harris_corner_cvip( I , threshold, std,alfa, maxsupress); % Display input image figure; imshow(I);title('Input image') % Display output image figure; imshow(CRF);title('Resultant image from corner response function');

The size of the gaussian is: 16 The threshold value is: 109468.843153

## CREDITS

Author: Mehrdad Alvandipour, July2017

Copyright © 2017-2018 Scott
E Umbaugh

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