An Automated Visual Inspection System for the Classification of the Phases of Ti-6Al-4V Titanium Alloy

Metallography is the science of studying the physical properties of metal microstructures, by means of microscopes. While traditional approaches involve the direct observation of the acquired images by human experts, Com-puter Vision techniques may help experts in the analysis of the inspected mate-rials. In this paper we present an automated system to classify the phases of a Titanium alloy, Ti-6Al-4V. Our system has been tested to analyze the final products of a Friction Stir Welding process, to study the states of the micro-structures of the welded material

Trends in Applied Intelligent Systems

This paper presents the detection and classification part of an industrial machine for automated assembly of decorative tessellae over patterned tiles that have significant reliefs. The machine consists of two vision systems for detecting the tiles and the tessellae, and a robotic manipulator to make the assembly. One of the vision systems detects the tessellae and the other one detects and classifies the tiles, finding the positions and orientations on the tiles where tessellae have to be mounted. Lateral illumination is used to enhance shadows and characterize the relief pattern. The shadow pattern is used as the main feature for classifying a tile to a model. The method works with a variety of models, is quite robust, and achieves very good classification results, as required for an industrial application