An Information System for Material Microstructures
This study presents an innovative information system designed for analyzing material microstructures, specifically focusing on cast iron. The core architecture includes advanced image preprocessing, feature extraction, and classification techniques using Support Vector Machines (SVM). The system has been validated with a dataset of 350 pre-classified images, achieving significant sensitivity in classification through a rigorous feature analysis. With positive user feedback, future work aims to enhance the feature set, handle multi-class images, and expand applications to various materials, fostering ongoing collaboration with materials scientists.
An Information System for Material Microstructures
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Presentation Transcript
An Information System for Material Microstructures What can CS/DB do for material sciences Kathrin Roberts, Karlsruhe Univ. Frank Mücklich, Saarland Univ., Material Sciences Ralf Schenkel, Gerhard Weikum, MPI Informatik
Motivation Class of this iron? A B C D E • Material properties depend on microstructure of the material • Microscopic images • 5 classes of cast iron(EN ISO 945:1994) Human experts needed!
System Architecture PID Java-Servlet Image Preprocessing Feature Extraction Classification (SVM) Oracle DB
Some Details on SVM d Mindestabstand X2 + + d - + d - + + d - - - X1 Represent training data by feature vectors Build separating hyperplane Classification by computing distance to hyperplane One SVM per class
Feature Vectors 90° 45° 135° 6 7 8 5 1 0° 4 3 2 • 14 Haralick Parameters [Haralick73]Statistics on black-white-transitions x
Feature Vectors • 6 Stereologic Parameters [Mücklich00]Statistics about connected areas of black pixels
Preliminary Experimental Results • 350 pre-classified images of cast iron • leave-one-out evaluation
Sensitivity Analysis Find features with most influence on classification Greedy algorithm: • Drop the feature with least influence on precision • Repeat until precision gets too low
Conclusion & Future Work • Fully functional system for classifying microstructures of cast iron • Users like it! • Extend feature set • Partition images with more than one class • Extend to other types of material • Continue collaboration with material scientists
