Abstract
This paper presents an implementation of a digital filtering inspection system applied on a paper pulp sheet production process. The automation of the inspection phase is particularly critical during this process and its solution is highly complex. The system is based on neural network learning, allowing a compromise between resolution and processing speed. The experimental results demonstrating the use of this algorithm for the visual detection of defects in images obtained from a real factory environment are presented. These results show that the developed learning method generates filters that fulfil the required inspection standard.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Campoy, P.: Nuevas Tendencias sobre Control Avanzado: Redes Neuronales, pp. 37–53, Fundacion Repsol Publicaciones, 1999.
Campoy, P.: Sistemas Inteligentes en la Inspeccin Visual, “Industria XXI” Revista ETSII, Número 0, Universidad Politcnica de Madrid, pp. 23–33, 2000.
Conners, R. Identifying and locating surface defects in wood, IEEE Transactions PAMI 5(6) (1983), pp 573–583.
Dewaele, P., Van Gool, L., and Oosterlinchk, A. Texture Inspection withself-adaptive convolution filters, Proceedings of the Ninth International Conference on Pattern Recognition, 1, 1988, pp 14–17.
Lee, C.S., Choi, C.H., Choi, J.Y., Kim, Y.K. and Choi, S.H., Feature extraction algorithm based on adaptive wavelet packet for surface detect classification, IEEE International Conference on Image Processing, 1996, pp. 673–675.
Normas ENCE: Technical Specification of the Product, Empresa Nacional de Celulosas, S.A., 1994.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Campoy-Cervera, P., Mun̄oz-García, D.F., Pen̄a, D., Calderón-Martínez, J.A. (2001). Automatic Generation of Digital Filters by NN Based Learning: An Application on Paper Pulp Inspection. In: Mira, J., Prieto, A. (eds) Bio-Inspired Applications of Connectionism. IWANN 2001. Lecture Notes in Computer Science, vol 2085. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45723-2_28
Download citation
DOI: https://doi.org/10.1007/3-540-45723-2_28
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-42237-2
Online ISBN: 978-3-540-45723-7
eBook Packages: Springer Book Archive