Computer-Aided Recognition of Defects in Welded Joints during Visual Inspections Based on Geometric Attributes; Russian Journal of Nondestructive Testing; Vol. 56, iss. 3

Computer-Aided Recognition of Defects in Welded Joints during Visual Inspections Based on Geometric Attributes; Russian Journal of Nondestructive Testing; Vol. 56, iss. 3

Bibliografski detalji
Parent link:	Russian Journal of Nondestructive Testing Vol. 56, iss. 3.— 2020.— [P. 259-267]
Glavni autor:	Muravyov (Murav’ev) S. V. Sergey Vasilyevich
Autor kompanije:	Национальный исследовательский Томский политехнический университет Инженерная школа информационных технологий и робототехники
Daljnji autori:	Pogadaeva E. Yu. Ekaterina Yurjevna
Sažetak:	Title screen An automated defect recognition algorithm is presented for detecting and classifying weld defects by photographic images. The proposed recognition algorithm selects a defective domain in a segmented image, extracts geometric features from the image, and relates the defect to one of six classes: no defect, cavity, longitudinal crack, transverse crack, burn-through, or multiple defect. The algorithm is implemented in the Matlab 2018b MathWorks environment and has been tested on 60 photographs of defects of various classes; the accuracy of recognition was 85%. Режим доступа: по договору с организацией-держателем ресурса
Jezik:	engleski
Izdano:	2020
Teme:	электронный ресурс труды учёных ТПУ weld defect segmentation classification image processing visual inspection сварные швы дефекты сегментация обработка изображений
Online pristup:	https://doi.org/10.1134/S1061830920030055
Format:	Elektronički Poglavlje knjige
KOHA link:	https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=662251

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