Abstract: The purpose of this paper is to
present a complete methodology based on a multidisciplinary approach,
that goes from the extraction of features till the classification of a
set of different portuguese granites. The set of tools to extract the
features that characterise polished surfaces of the granites is mainly
based on mathematical morphology. The classification methodology is
based on a genetic algorithm capable of search the input feature space
used by the nearest neighbour rule classifier. Results show that is
adequate to perform feature reduction and simultaneous improve the
recognition rate. Moreover, the present methodology represents a robust
strategy to understand the proper nature of the images treated, and
their discriminant features.
Keywords: Portuguese grey Granites,
Feature Extraction, Mathematical Morphology, Evolutionary Computation,
Feature reduction, Genetic Algorithms, Nearest neighbour rule
classifiers (k-NNR).
Cited
by:
º Mujica-V,
V.E.; Sisalem, D.; Popescu-Zaletin, R. "NEURAL: A
Self-Organizing Routing Algorithm for Ad Hoc Networks", in
WiOpt´05 - Third International Symposium on Modeling and
Optimization in Mobile, Ad Hoc, and Wireless Networks, pp. 259-266,
Trentino, Italy, April 2005.
º Nicolai Marquardt,
"Swarm-Intelligence: Modelle und Anwendungen", Seminar:
VR-Technologien, Prof. Dr. B. Fröhlich, Bauhaus-Universität
Weimar, Jan. 2004.
º Nicolai Marquardt, "Intelligenz
von Schwärmen: Grundlagen, Simulations, Modelle und Anwendungen",
Bauhaus-Universität Weimar, Jan. 2004.
º
Hocenski, Zeljko; Nyarko, Emmanuel Karlo, "Surface Control of Ceramic
Tiles using Neural Networks approach", in Proceedings of the 2002 IEEE
International Symposium on Industrial Electronics, ISIE 2002 / Carlo
Cecati (ed). - L Aquila : University of L Aquila , 2002. 1731-1734.
º Steven J. Schafrik, "A New
Style of Simulation Model for Mining Systems", MSc Thesis, Faculty of
the Virginia Polytechnic Institute and State University (Mining and
Minerals Engineering), VA, USA, 2001.
º Keith Price, "Annotated
Computer Vision Bibliography", Chapter 19 (19.9.3), Implementations and
Applications of Vision Systems, Databases, Hardware and Software.
Institute for Robotics and Intelligent Systems, School of Engineering
(IRIS), University of Southern California, USA.
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