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A Data Clustering Approach for Automated Optical Inspection of Metal Work Pieces
- This paper describes the use of the single-linkage
hierarchical clustering method in outlier detection for
manufactured metal work pieces. The main goal of the study is
to group defects that occur 5 mm into a work piece from the
edge, i.e., the border of the metal work piece. The goal is to
remove defects outside the area of interest as outliers.This paper describes the use of the single-linkage
hierarchical clustering method in outlier detection for
manufactured metal work pieces. The main goal of the study is
to group defects that occur 5 mm into a work piece from the
edge, i.e., the border of the metal work piece. The goal is to
remove defects outside the area of interest as outliers.
According to the assumptions made for the performance
criteria, the single-linkage method has achieved better results
compared to other agglomeration methods.…
| Author: | Stephan TrahaschORCiDGND, Tobias LauerGND, Ruth Zibello |
|---|---|
| Year of Publication: | 2018 |
| Pagenumber: | 5 |
| ISBN: | 978-1-61208-631-6 |
| Language: | English |
| Parent Title (English): | ALLDATA 2018, The Fourth International Conference on Big Data, Small Data, Linked Data and Open Data |
| First Page: | 64 |
| Last Page: | 68 |
| Document Type: | Conference Proceeding |
| Institutes: | Bibliografie |
| Acces Right: | Zugriffsbeschränkt |
| Release Date: | 2019/01/08 |
| Licence (German): |  Es gilt das UrhG |