Colour moment method to extract features from endoscopic gastritis digitized images

Abstract

Gastritis is a disorder that occur when the stomach lining become swollen, a condition of inflammation or irritation of stomach lining. Normally, visual interpretation or pathology diagnosis is applied to detect any abnormalities in stomach. In this project, computer-aided diagnosis which required image features to classify the endoscopic gastritis digitized image. It is a target to extract features using colour moment method. For image classification, WEKA learning machine is used as multiple classifiers to assort the image into its class of normal or abnormal. Classifier with higher percentage of classification rate is the most accurate.