Artificial neural networks for automated quality control of textile seams

被引：36

作者：

Bahlmann, C ^{[1
]}

Heidemann, G ^{[1
]}

Ritter, H ^{[1
]}

机构：

[1] Univ Bielefeld, Tech Fak, AG Neuroinformat, D-33615 Bielefeld, Germany

来源：

PATTERN RECOGNITION | 1999年 / 32卷 / 06期

关键词：

neural networks; self-organizing feature maps (SOFM); textile seams; quality control; feature selection;

D O I：

10.1016/S0031-3203(98)00128-9

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We present a method for an automated quality control of textile seams, which is aimed to establish a standardized quality measure and to lower coals in manufacturing. The system consists of a suitable image acquisition setup, an algorithm for locating the seam, a feature extraction stage and a neural network of the self-organizing map type for feature classification. A procedure to select an optimized feature set carrying the information relevant for classification is described. (C) 1999 Pattern Recognition Society. Published by Elsevier Science Ltd, All rights reserved.

引用

页码：1049 / 1060

页数：12

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