In this work, computer vision and machine learning techniques are used to identify and classify surface defects of used gun barrels. Internal surface images of the gun barrel with surface defects were captured, labelled and stored in a database. There were five classes assigned namely normal wear, erosion, corrosive pitting, rust and nodefect.