HMM-Based Defect Localization in Wire Ropes --- A New Approach to Unusual Subsequence Recognition

Authors:
Esther-Sabrina Platzer;Josef Nägele;Karl-Heinz Wehking;Joachim Denzler
Affiliations:
Chair for Computer Vision, Friedrich Schiller University of Jena,;Institute of Mechanical Handling and Logistics, University Stuttgart,;Institute of Mechanical Handling and Logistics, University Stuttgart,;Chair for Computer Vision, Friedrich Schiller University of Jena,
Venue:
Proceedings of the 31st DAGM Symposium on Pattern Recognition
Year:
2009

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Abstract

Automatic visual inspection has become an important application of pattern recognition, as it supports the human in this demanding and often dangerous work. Nevertheless, often missing abnormal or defective samples prohibit a supervised learning of defect models. For this reason, techniques known as one-class classification and novelty- or unusual event detection have arisen in the past years. This paper presents a new strategy to employ Hidden Markov models for defect localization in wire ropes. It is shown, that the Viterbi scores can be used as indicator for unusual subsequences. This prevents a partition of the signal into sufficient small signal windows at cost of the temporal context. Our results outperform recent time-invariant one-class classification approaches and depict a great advance for an automatic visual inspection of wire ropes.