Iris Recognition with Python

In this project, we explore Iris Recognition using Python by implementing MATLAB-inspired code. The libraries used are critical for visualizing and processing iris images.

  1. matplotlib.pyplot: This module, part of the matplotlib library, mimics MATLAB's global style. It simplifies the transition for users familiar with MATLAB by integrating functions and classes from NumPy and matplotlib. In our project, pyplot is used to plot images and define circles representing the pupil and iris edges. It's also useful for displaying the processed images during the recognition process.

  2. OpenCV: OpenCV is an open-source computer vision library that provides more than 2500 optimized algorithms for applications like face recognition, object detection, and behavior classification in videos. In this project, OpenCV is primarily used for Hough Circle Detection. This technique helps identify the center and boundaries of the pupil and iris, crucial for accurate iris recognition.

By using these libraries together, we can create a functional and efficient iris recognition system that processes and identifies the unique features of the iris for biometric applications.