shubhangb97/irisrecognition

Iris Recognition implementation using PCA and LDA, along with some preprocessing on the dataset

Iris Recognition

• In this project, we use the methods of PCA(principal component analysis) and fisher LDA to make an iris recognition system. We use PCA on an image after pre processing to reduce the dimensionality of the image, followed by a LDA based classifier.
• Its advantages over the traditional approaches which use Wavelet and Hough transforms on iris images, followed by various matching algorithms is that it allows for a much faster recognition combined with a high accuracy.
• For more details about our method and its accuracy, please refer to the presentation.
• This repository was a part of a group project for the course CS663 Digital image processing at IITB