On the Suitability of Different Features for Anomaly Detection in Wire Ropes

Platzer, Esther-Sabrina; Süße, Herbert; Nägele, Josef; Wehking, Karl-Heinz; Denzler, Joachim

doi:10.1007/978-3-642-11840-1_22

Cited by 18 publications

(17 citation statements)

References 14 publications

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“…Fig. 2 shows an exemplary detection result obtained with our implementation of the approach of Platzer et al [8]. Obviously, just a small part of the defect was recovered.…”

Section: Related Workmentioning

confidence: 98%

“…It is hard to obtain defective examples from a real ropeway, especially due to the strict rules for a regular visual examination [6]. In order to cope with the missing abnormal training material, one-class classification approaches, also known as novelty detection or unusual event detection, have arisen the past years [7,1,3,4,8].…”

Section: (C)mentioning

confidence: 99%

“…2. Result of the automatic defect detection in wire ropes presented in [8]. The white window borders the rope region, which was classified as potential defect.…”

Section: Related Workmentioning

confidence: 99%

“…Potential defects in ropes are identified by an outlier detection scheme. The work is extended in [8] by a comparison of different features. The approach allows a defect detection in wire ropes, but its localization ability is strongly restricted.…”

Section: Related Workmentioning

confidence: 99%

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

Platzer

Nägele

Wehking

et al. 2009

Lecture Notes in Computer Science

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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.

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“…Fig. 2 shows an exemplary detection result obtained with our implementation of the approach of Platzer et al [8]. Obviously, just a small part of the defect was recovered.…”

Section: Related Workmentioning

confidence: 98%

Section: (C)mentioning

confidence: 99%

“…2. Result of the automatic defect detection in wire ropes presented in [8]. The white window borders the rope region, which was classified as potential defect.…”

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

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

Platzer

Nägele

Wehking

et al. 2009

Lecture Notes in Computer Science

Self Cite

View full text Add to dashboard Cite

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“…In general, these approaches are highly dependent on their choice of features used to represent the intact class. Platzer et al [7] compared the performance of different textural features for the problem of defect detection in wire rope surfaces. Their results underline the importance of context information for the problem of surface defect detection, especially with respect to the complex structure of wire ropes.…”

Section: Introductionmentioning

confidence: 99%

Combining Structure and Appearance for Anomaly Detection in Wire Ropes

Wacker

Denzler

2011

Computer Analysis of Images and Patterns

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Abstract. We present a new approach for anomaly detection in the context of visual surface inspection. In contrast to existing, purely appearancebased approaches, we explicitly integrate information about the object geometry. The method is tested using the example of wire rope inspection as this is a very challenging problem. A perfectly regular 3d model of the rope is aligned with a sequence of 2d rope images to establish a direct connection between object geometry and observed rope appearance. The surface appearance can be physically explained by the rendering equation. Without a need for knowledge about the illumination setting or the reflectance properties of the material we are able to sample the rendering equation. This results in a probabilistic appearance model. The density serves as description for normal surface variations and allows a robust localization of rope surface defects. We evaluate our approach on real-world data from real ropeways. The accuracy of our approach is comparable to that of a human expert and outperforms all other existing approaches. It has an accuracy of 95% and a low false-alarm-rate of 1.5%, whereupon no single defect is missed.

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Nondestructive Testing of Composite Materials

Zhang

2011

Handbook of Multiphase Polymer Systems

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On the Suitability of Different Features for Anomaly Detection in Wire Ropes

Cited by 18 publications

References 14 publications

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

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

Combining Structure and Appearance for Anomaly Detection in Wire Ropes

Nondestructive Testing of Composite Materials

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