Hi samarpit,
I understand that you want to implement an iris recognition system in MATLAB
I assume you have access to a dataset of eye images for testing and are familiar with basic image processing concepts.
In order to implement an iris recognition system, you can follow the below steps:
Preprocess the Image:
Load the eye image and preprocess it to enhance features. This includes converting to grayscale and applying histogram equalization to improve contrast.
I = imread('eye_image.jpg');
if size(I, 3) == 3
I = rgb2gray(I);
end
I = histeq(I); % Histogram equalization
Segment the Iris:
Use edge detection and the Hough Transform to detect the circular boundary of the iris and pupil. This helps isolate the iris region.
edges = edge(I, 'canny');
[centers, radii] = imfindcircles(edges, [20 50], 'ObjectPolarity', 'dark');
Normalize the Iris:
Transform the segmented iris region to a fixed dimension using polar coordinates. This normalization helps in comparing different irises.
% Example function call (pseudo-code)
normalizedIris = normalizeIris(I, centers, radii);
Extract Features:
Apply Gabor filters to extract unique features from the normalized iris image. These features form the basis for recognition.
gaborArray = gabor([4 8], [0 90]);
gaborMag = imgaborfilt(normalizedIris, gaborArray);
Match and Recognize:
Compare the extracted features with a database of known iris features using a suitable distance metric to recognize the iris.
% Example matching function (pseudo-code)
matchScore = compareFeatures(gaborMag, irisDatabase);
Refer to the documentation of "imfindcircles" function to know more about the properties supported: https://www.mathworks.com/help/images/ref/imfindcircles.html
Hope this helps!
