Publicaciones Científico Tecnológicas

@article{bereciartua2004surface,
title = {Surface inspection of polyurethane foam by image processing and artificial neural networks techniques.},
author = {Arantza Bereciartua-Pérez and Jose A. Gutiérrez-Olabarria and Artzai Picón-Ruiz and ALFONSO MAESTRO MARTÍNEZ},
url = {https://computervision.tecnalia.com/wp-content/uploads/2012/12/2004_-Surface-Inspection-of-polyurethane-foam-by-image-processing-and-Artificial-Neural-Networks-Techniques-.pdf},
year = {2004},
date = {2004-01-01},
journal = {WSEAS Transactions on Circuits and Systems},
volume = {3},
number = {10},
pages = {2122--2127},
abstract = {Quality assurance is a necessity in the industrial processes. The machine vision technology is an efficient technology for the reliable and fast control of different types of products. This technology allows obtaining a big amount of visual information, superficial and dimensional at a high speed. The objective of this article is to describe a successful application of machine vision technology in a Foam production, a productive sector where this technology is scarcely inserted. The aim of this project is to obtain on-line visual parameters of the process in order to modify the variables of production immediately in an automated way. Those parameters were obtained off-line by means of human visual inspection two days later in a laboratory analysis before this project. The difficulty lies in the fact that visual characteristics of both samples (on-line and off-line) are very different.


Surface inspection of polyurethane foam by image processing and artificial neural networks techniques | Request PDF. Available from: https://www.researchgate.net/publication/261858641_Surface_inspection_of_polyurethane_foam_by_image_processing_and_artificial_neural_networks_techniques [accessed Jul 20 2018].},
keywords = {darkfield, foam, machine vision, neural network, pore, quality control, surface control},
pubstate = {published},
tppubtype = {article}
}