Histogram-Based Descriptor Subset Selection for Visual Recognition of Industrial Parts
dc.contributor.author | Merino Bermejo, Ibon | |
dc.contributor.author | Azpiazu Lozano, Jon | |
dc.contributor.author | Remazeilles, Anthony | |
dc.contributor.author | Sierra Araujo, Basilio ![]() | |
dc.date.accessioned | 2020-06-17T12:16:02Z | |
dc.date.available | 2020-06-17T12:16:02Z | |
dc.date.issued | 2020-05-22 | |
dc.identifier.citation | Applied Sciences 10(11) : (2020) // Article ID 3701 | es_ES |
dc.identifier.issn | 2076-3417 | |
dc.identifier.uri | http://hdl.handle.net/10810/43994 | |
dc.description.abstract | This article deals with the 2D image-based recognition of industrial parts. Methods based on histograms are well known and widely used, but it is hard to find the best combination of histograms, most distinctive for instance, for each situation and without a high user expertise. We proposed a descriptor subset selection technique that automatically selects the most appropriate descriptor combination, and that outperforms approach involving single descriptors. We have considered both backward and forward mechanisms. Furthermore, to recognize the industrial parts a supervised classification is used with the global descriptors as predictors. Several class approaches are compared. Given our application, the best results are obtained with the Support Vector Machine with a combination of descriptors increasing the F1 by 0.031 with respect to the best descriptor alone. | es_ES |
dc.description.sponsorship | This paper has been supported by the project SHERLOCK under the European Union’s Horizon 2020 Research & Innovation programme, grant agreement No. 820689. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | MDPI | es_ES |
dc.relation | info:eu-repo/grantAgreement/EC/H2020/820689 | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | |
dc.subject | computer vision | es_ES |
dc.subject | feature descriptor | es_ES |
dc.subject | histogram | es_ES |
dc.subject | feature subset selection | es_ES |
dc.subject | industrial objects | es_ES |
dc.title | Histogram-Based Descriptor Subset Selection for Visual Recognition of Industrial Parts | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.date.updated | 2020-06-16T04:48:02Z | |
dc.rights.holder | 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). | es_ES |
dc.relation.publisherversion | https://www.mdpi.com/2076-3417/10/11/3701/htm | es_ES |
dc.identifier.doi | 10.3390/app10113701 | |
dc.contributor.funder | European Commission | |
dc.departamentoes | Ciencia de la computación e inteligencia artificial | |
dc.departamentoeu | Konputazio zientziak eta adimen artifiziala |
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Except where otherwise noted, this item's license is described as 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).