Diabetes Detection based on Iris abnormal

ABSTRACT:

For clinical diagnosis, Iris image analysis is one of the most efficient non-invasive diagnosis method which helps to determine the health status of organs. Though correct and timely diagnosis is critical, it is very essential requirement of medical science. From the literature survey that we have done, is observed that lot of modern technologies also fails in diagnose disease correctly. From different perspectives this attempt explore the area of diagnosis. Iridodiagnosis is the branch of medical science, with the help of which different diseases can be detected. Initially the images of eye are captured, database is created with their clinical history, features are found out and finally the classification is done whether the diabetic is present or not. Several classification methods can be used for training and classification purpose. We have implemented Machine learning KNN model, which will be useful in the diagnosis field which is faster and user friendly.

PROJECT OUTPUT VIDEO:

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS:

• System            : Pentium Dual Core.

• Hard Disk       : 120 GB.

• Monitor          : 15’’ LED

• Input Devices : Keyboard, Mouse

• Ram                : 1GB.

SOFTWARE REQUIREMENTS:

• Operating system : Windows 7.

• Coding Language : MATLAB.

• Tool                      : MATLAB R2013A