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A Public Fabric Database for Defect Detection Methods and Results

Silvestre-Blanes Javier, Albero-Albero Teresa, Miralles Ignacio, Pérez-Llorens Rubén, Moreno Jorge

Autex Research Journal

2019

Vol. 19, no. 4

363--374

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.

Dynamiczna kontrola jakości tkanin

Lewandowski S.

Przegląd Włókienniczy - Włókno, Odzież, Skóra

2007

nr 8

63-64

Dynamic control of fabrics, based on systems using artificial neural networks was presented. It has been found out that the adaptation of the technology linking the digital processing of the image together with artificial neural networks was the very valuable tool serving for carrying out of dynamic control of errors of fabrics and identification of their kinds.