Iris Color Detection with Raspberry Pi

An innovative project combines a Raspberry Pi 3 Model B+ and a camera module to analyze iris color using OpenCV, with potential applications in healthcare.

Project Background

Student Srikrishna Karthick, working at ISRO, developed this solution for a science event in India. The goal was to automate eye color analysis during genetics demonstrations involving fruit flies.

Technology Used

• Raspberry Pi 3 Model B+
• Raspberry Pi Camera Module 3
• OpenCV for image processing
• Face and iris detection algorithms

Technical Workflow

The system leverages a combination of advanced techniques:

• Detects faces and eyes using OpenCV Haar cascades
• Locates the iris through a circular search approach inspired by Daugman
• Filters non-iris regions using brightness and saturation thresholds
• Applies k-means clustering in both RGB and HSV color spaces
• Classifies colors into categories such as dark brown, blue, or green

Results and Success

The project processed 350 samples without errors during the event. The tested algorithms demonstrated high reliability, leveraging globally recognized methods such as the Daugman algorithm.

Key Advantages

• Detection of secondary colors invisible to the human eye
• Robust system with no hardware overheating
• Simple interface triggered via a GPIO button

Future Applications

The team plans to adapt the codebase for medical diagnostics:

• Cataract detection
• Diagnosis of fungal eye infections
• Extension to other body tissues

A team of students has already been working on expanding the project for the past three months.

Acknowledgments

Srikrishna thanks Dr. Prasanna Katti and the IISER Tirupati committee for their technical support. The project was featured in issue 168 of the Raspberry Pi Official Magazine.

Additional Resources

For more similar projects, visit the Raspberry Pi Official Magazine or subscribe to the print service for additional benefits.

Original source: Raspberry Pi News