An automatic system to surface defect classification of hot rolled steel

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dc.contributor.authorBoudiaf, Adel
dc.contributor.authorMoussaoui, Abdelkrim
dc.contributor.authorZaghdoudi, Rachid
dc.contributor.authorMentouri, Zoheir
dc.contributor.authorSaadoune, Achour
dc.date.accessioned2019-05-23T10:20:49Z
dc.date.available2019-05-23T10:20:49Z
dc.date.issued2018-12-10
dc.descriptionInternational Symposium on Mechatronics and Renewable Energies El-Oued 10- 11 December 2018en_US
dc.description.abstractThe primary objective of this paper is to develop an automatic surface defect inspection system for hot-rolled flat steel The proposed technique consists of four major steps. The proposed technique consists of four major steps. The first step is image acquisition. The second step is features extraction of image by Histogram of oriented gradients (HOG). In the third step the principal component analysis (PCA) is applied on the HOG descriptor to reduce the dimensionality of the feature vector. In the final step the K- nearest neighbor classifier (KNN) is used to classify the different steel surface defects. The experimental results showed that the proposed steel inspection system which is based on KNN classifier provide a better results and recognition accuracy of 91.12%.en_US
dc.identifier.urihttp://dspace.univ-eloued.dz/handle/123456789/1390
dc.language.isoenen_US
dc.publisherUniversity of Eloued جامعة الواديen_US
dc.subjectIndustrial vision, the K- nearest neighbor classifier, classification of surface defects, Histogram of Oriented Gradients (HOG), Principal Component Analysis (PCA)en_US
dc.titleAn automatic system to surface defect classification of hot rolled steelen_US
dc.typeOtheren_US

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