Object recognition in industrial environments using support vector machines and artificial neural networks

Original Article

DOI: 10.1007/s00170-009-2313-3

Cite this article as:
Barry, T.J. & Nagarajah, C.R. Int J Adv Manuf Technol (2010) 48: 815. doi:10.1007/s00170-009-2313-3

Abstract

This paper presents a comparison between Artificial Neural Networks and Support Vector Machines in the application of classifying automotive wheels in an industrial environment. Performance of these two approaches over a range of classifier parameters on a data set pre-processed in multiple ways has been evaluated and the results analysed. Results indicate that the best performance is obtained using a support vector machine approach incorporating a linear kernel.

Keywords

Artificial neural networks Support vector machines Feature extraction Wheel identification 

Copyright information

© Springer-Verlag London Limited 2009

Authors and Affiliations

  1. 1.Faculty of Engineering and Industrial SciencesSwinburne University of TechnologyHawthornAustralia

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