Retinal Authentication System

Project Title

Retinal Authentication System

Project Area of Specialization Artificial IntelligenceProject Summary

The system contains iris security, face detection, firebase security. To verify the authorized person. The person took the picture of retina through phone and sends it to the firebase. Then firebase verifies the retina through trained models and check whether the person is authorized or not. In the firebase security side, the System which accesses the firebase is secured face detection and retinal system. The face detection system open the system and the system runs only when the retinal system is running if the person move away from the system it will turn off the screen of a system.

Project Objectives

The goal of this project is basically to ensure the security of safe and items in a vault or anything through that door. Our project will mainly focus on the following objectives: To send a retinal picture of an eye through a mobile app to a firebase system. Then system verifies it through the firebase system. The system only accepts the human retinal picture through a camera and rejects every picture an eye which has eye picture on a page. For firebase security the system which accesses the firebase can be accessed by face detection and the system will be accessible if the person sees in the camera of a system.

The goal of this project is basically to ensure the security of safe and items in a vault or anything through that door. Our project will mainly focus on the following objectives:

1. To send a retinal picture of an eye through a mobile app to a firebase system.
2. Then system verifies it through the firebase system.
3. The system only accepts the human retinal picture through a camera and rejects every picture an eye which has eye picture on a page.
4. For firebase security the system which accesses the firebase can be accessed by face detection and the system will be accessible if the person sees in the camera of a system.

Project Implementation Method

Project is implemented using python(jupyter notebook)

1) Face detection and eye detection for system security is implemented on the system 

2) for retial authentication system we first trained our model to differ between iris and non iris images

3) these images are then run via script to check the iris we got from the users phone is verified or not

Benefits of the Project

It is a security feature in biometric sector. Which can further implemented in various areas where security is needed.

Technical Details of Final Deliverable

You can login in your System with face detection and remained login when you have eye contact with the camera of your system. The moment your eye contact broken system gets into sleep state. these are the techincal details of the security of the system where verifications are done. On the other hand user login via app and sends his iris image using his own camera then sends it to firebase and check whether he is authorised or not. App is just for the prototype for the working of the whole project app can be replaced with the components where security is needed.

Final Deliverable of the Project Software SystemCore Industry SecurityOther Industries IT , Medical , Finance , Legal , Telecommunication Core Technology Artificial Intelligence(AI)Other Technologies Internet of Things (IoT)Sustainable Development Goals Partnerships to achieve the GoalRequired Resources

Elapsed time in (days or weeks or month or quarter) since start of the project	Milestone	Deliverable
Month 1	Dataset	Model train for detection of iris
Month 2	App development	Where you can send you eye image to firebase
Month 3	face detection	design algorithm and implement on the system
Month 4	eye detection	design algorithm and implement on the system
Month 5	download the dataset from firebase via script	the images on the firebase download and store in the specific folder in the path given in the script
Month 6	process the image and identify whether its verified user or not	process the image and identify whether its verified user or not and sends the message to the user.
Month 7	process the image and identify whether its verified user or not	process the image and identify whether its verified user or not and sends the message to the user.
Month 8	Merge the whole project and start testing	Tests and fix the bugs to smoothly runs the project.