Iris Detection and Recognition: MATLAB Code

This page provides a step-by-step guide with MATLAB code for eye iris detection and recognition.

clear all;
close all;
clc;

% Reading the image
Img=imread('002L_1.png');

%% Pre-Processing and Normalization
figure;
imshow(Img);
title('INPUT EYE IMAGE');

%% Step 1: Converting to Grayscale from RGB
Gray_imag=rgb2gray(Img);
figure;
imshow(Gray_imag);
title('IMAGE after Gray conversion');

% Deleting extra portion
t2=Gray_imag(:,65:708);
t3=t2(18:563,:);
figure;
imshow(t3);
title('IMAGE after Deleting extra portion');

%% Step 2: Resizing the image (546x644) to 512 x 512
t4=imresize(t3,[512,512],'bilinear');
figure;
imshow(t4);
title('IMAGE after resize');

%% Step 3: Histogram Equalization
Hist_eq_img = histeq(t4,512);
figure;
imshow(Hist_eq_img);
title('IMAGE after Histogram Equalization');

% Step 4: Gaussian Filtering
G = fspecial('gaussian',[512 512],20); %Filter it
Hist_eq_img=double(Hist_eq_img);
Ig = imfilter(Hist_eq_img,G,'same');
%Display

%% Step 5: Canny Edge detection
BW2 = edge(Ig,'canny',0.53,1);
figure;
imshow(BW2);
title('IMAGE after canny edge detection');

Step-by-Step Image Processing

Here’s a visual breakdown of the image processing steps:

STEP 1: RGB image to grayscale conversion

STEP 2: Image Resize

STEP 3: Histogram Equalization

STEP 4: GAUSSIAN FILTERING

STEP 5: CANNY EDGE DETECTION

Downloads

Input EYE Image:

Click to download (No direct link provided in original text, assume user has this)

External reference

• A Novel Approach to Iris Localization for Iris Biometric Processing