Abstract
The goals of this paper is to develop effective algorithms to achieve acceptable performance in what we call Visually Detectable Defects (V.D.D); and also to define from systems concepts a test strategy. The main problem in V.D.D. has been finally identified as that of the detection and labelling of subtle changes in the texture of an image. In consequence, none of the standard procedures for texture discrimination gave good results, so that increasing the complexity of the process was decided upon, to provide a new decision level.
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Candela, S. Transformaciones de Campo Receptivo Variable en Proceso de Imagenes y Visión Artificial. Tesis Doctoral. Nov 1987.
Candela, S., Muñoz, J., Alayon, F., Garcia C. Un Sistema de Visión para la Detección de Defectos.Actas de Panel'92 p 240–247. Las Palmas de G. Canaria. 1992. Universidad de Las Palmas de Gran Canaria.
Conners, R. Identifying and Locating Surface Defects in Wood: Part of an Automated Lumber Processing System. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.Pami-5, No 6, November 1983.
Haralick, R. Statistical and Structural Approaches to Texture. Proceedings of the IEEE, vol 67, no 5, May 1979.
Muñoz Blanco, J. A.”Jerarquizaci ón de estructuras de nivel bajo y medio para reconocimiento visual. Aplicaciones a texturas y formas. Tesis Doctoral. 1987.
Rao, K., Ahmed, N. Orthogonal Transforms for Digital Signal Processing. IEEE International Conference on Acustics, Speech and Signal Processing P 136–40, 1976.
Santana, O., Candela, S., Moreno-Diaz, R. Computer non-linear and Algorithmic Simulation of Static Retinal Processes. 6th International Congress of Cybernetics and Systems. Paris. 1984.
Unser, M., Coulon, F. Detection of Defects by Texture Monitoring in Automatic Visual Inspection. Proceedings of The 2md International Conference on Robot Vision and Sensory Controls November 1982. Stuttgart, Germany.
Wang, Li.; D. C. He. “A new statistical approach for texture analysis”. Photogrammetric Engineering and Remote Sensing, vol. 56, N∘ 1, pp 61–66. 1990.
Wang, L.; and D. He. “Texture Classification Using Texture Spectrum”. Pattern Recognition”. 1990.
Weszka, J. S.; Dyer and A. Rosenfeld.”A Comparative Study of Texture Measures for Terrain Classification. IEEE Transaction On Systems, Man, and Cybernetics. 1976.
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© 1994 Springer-Verlag Berlin Heidelberg
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Muñoz, J., Garcia, C., Alayon, F., Candela, S. (1994). Systems concept for visual texture change detection strategy. In: Pichler, F., Moreno Díaz, R. (eds) Computer Aided Systems Theory — EUROCAST '93. EUROCAST 1993. Lecture Notes in Computer Science, vol 763. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-57601-0_62
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DOI: https://doi.org/10.1007/3-540-57601-0_62
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