Comparison of Different Supervisied Classifiers in Detection of Microaneurysms

Diabetes is a rapidly increasing illness around the world. It can further cause diabetic rethinopathy(DR). If not treated properly it can make a person blind. Therefore a early detection system for (DR) is required which can be done by detecting abnormalities in eye known as microaneurysms. The main objective of this paper is to find out how different supervised classifiers responds to our morphological operation algorithm of detection of microaneurysms. The performances of the classifiers are examined by the images obtained from databse DIARETDB1 which also gives ground truths. DOI: 10.17762/ijritcc2321-8169.160413