Classification of Medical Images Using Support Vector Machine

The proposed work is to develop an automatic tool to identify microbiological types without human supervision. Generally Bacteriophage (phage) typing & Fluorescent imaging methods are used to extract representative feature profiles and bacterial types are identified by human experts by reading the feature profiles. These methods are time consuming and prone to errors. In this proposed work, the features of the bacterial image are extracted and Support Vector Machine (SVM) is used for classifying the Bacterial types. Support Vector Machines have high approximation capability and much faster convergence.