A Public Fabric Database for Defect Detection Methods and Results

The use of image processing for the detection and classification of defects has been a reality for some time in science and industry. New methods are continually being presented to improve every aspect of this process. However, these new approaches are applied to a small, private collection of image...

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Bibliographic Details
Main Authors: Silvestre-Blanes Javier, Albero-Albero Teresa, Miralles Ignacio, Pérez-Llorens Rubén, Moreno Jorge
Format: Article
Language:English
Published: Sciendo 2019-12-01
Series:Autex Research Journal
Subjects:
Online Access:https://doi.org/10.2478/aut-2019-0035
Description
Summary:The use of image processing for the detection and classification of defects has been a reality for some time in science and industry. New methods are continually being presented to improve every aspect of this process. However, these new approaches are applied to a small, private collection of images, which makes a real comparative study of these methods very difficult. The objective of this paper was to compile a public annotated benchmark, that is, an extensive set of images with and without defects, and make these public, to enable the direct comparison of detection and classification methods. Moreover, different methods are reviewed and one of these is applied to the set of images; the results of which are also presented in this paper.
ISSN:2300-0929