iron ores; ore mineralogy; particle morphology; expert systems; artificial intelligence
Abstract :
[en] Brazilian iron ores are predominantly hematitic and may have different textures. In the mining industry, their microstructural characterization is manually performed, by analyzing samples under an optical microscope to identify the hematite textures and estimate their fractions and crystal size. This procedure is subjective and consequently susceptible to random and systematic errors. The present paper proposes an automatic method for the identification, measurement and classification of hematite crystals in iron ore according to their textural types. The method exploits the use of circularly polarized light to amplify brightness and color differences among hematite crystals, allowing their individualization, and the subsequent morphological analysis and classification into granular, lamellar or lobular classes. The classifier was tested with more than 5400 crystals, reaching a global success rate close to 98%, and success rates per class above 96%.
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Bibliography
Beucher, S., Lantuéjoul, C., Use of watersheds in contour detection (1979) Proceedings of International Workshop on Image Processing, Real-time Edge and Motion Detection/estimation, pp. 21-212. , CCETT/IRISA, Rennes
Canny, J., A computational approach to edge detection (1986) IEEE Trans. Pattern Anal. Mach. Intell., 8 (6), pp. 679-698
Chen, Q., Yang, X., Petriu, E.M., Watershed segmentation for binary images with different distance transforms (2004) Proceedings - 3rd IEEE International Workshop on Haptic, Audio and Visual Environments and their Applications - HAVE 2004, pp. 111-116. , Proceedings - 3rd IEEE International Workshop on Haptic, Audio and Visual Environments and their Applications - HAVE 2004
Criddle, A.J., Stanley, C.J., (1993) Quantitative Data File for Ore Minerals, , 3rd ed. Chapman & Hall London
Danz, R., Gretscher, P., C-DIC: A new microscopy method for rational study of phase structures in incident light arrangement (2004) Thin Solid Films, 462-463, pp. 257-262
Donskoi, E., Suthers, S.P., Fradd, S.B., Young, J.M., Campbell, J.J., Raynlyn, T.D., Clout, J.M.F., Utilization of optical image analysis and automatic texture classification for iron ore particle characterisation (2007) Minerals Engineering, 20 (5), pp. 461-471. , DOI 10.1016/j.mineng.2006.12.005, PII S0892687506003190
Duda, R.O., Hart, P.E., Stork, D.G., (2001) Pattern Classification, , 2nd ed. Wiley-Interscience New York
Fisher, R.A., The use of multiple measurements in taxonomic problems (1936) Ann. Eugenics, 7, pp. 179-188
Glazer, A.M., Lewis, J.G., Kaminsky, W., An automatic optical imaging system for biréfringent media (1996) Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 452 (1955), pp. 2751-2765
Gomes, O.D.F.M., Paciornik, S., Automatic classification of graphite in cast iron (2005) Microscopy and Microanalysis, 11 (4), pp. 363-371. , DOI 10.1017/S1431927605050415
Gomes O. .D., .M., Paciornik, S., Iron ore quantitative characterization through reflected light-scanning electron co-site microscopy (2008) Proceedings of Ninth International Congress on Applied Mineralogy, pp. 699-702. , AusIMM, Brisbane
Gomes O. .D., .M., Paciornik, S., RLM-SEM co-site microscopy applied to iron ore characterization (2008) Annals of 2nd International Symposium on Iron Ore, pp. 218-224. , ABM, São Luís
Gomes O. .D., .M., Paciornik, S., Multimodal microscopy for ore characterization (2012) Scanning Electron Microscopy, pp. 313-334. , http://www.intechopen.com/books/scanning-electron-microscopy/ multimodal-microscopy-for-ore-characterization, Kazmiruk, V. (Ed.) InTech, Rijeka
Gomes O. .D., .M., Paciornik, S., Iglesias J. .C., .A., A simple methodology for identifying hematite grains under polarized reflected light microscopy (2010) Proceedings of 17th International Conference on Systems, Signals and Image Processing - IWSSIP 2010, pp. 428-431. , EdUFF, Rio de Janeiro
Gribble, C., Hall, A.J., (1992) Optical Mineralogy: Principles and Practice, , UCL Press London
Grum, J., Sturm, R., Computer supported recognition of graphite particle forms in cast iron (1995) Acta Stereologica, 14, pp. 91-96
Higgins, M.D., Imaging birefringent minerals without extinction using circularly polarized light (2010) Can. Mineral., 48, pp. 231-235
Iglesias, J.C.A., Gomes, O.D.M., Paciornik, S., Automatic recognition of hematite grains under polarized reflected light microscopy through image analysis (2011) Miner. Eng., 24 (12), pp. 1264-1270
Jain, A.K., Duin, R.P.W., Mao, J., Statistical pattern recognition: A review (2000) IEEE Transactions on Pattern Analysis and Machine Intelligence, 22 (1), pp. 4-37. , DOI 10.1109/34.824819
Libaneo, C.A.F., Kaneko, K.M., Coelho, L.H.T., Purificação, E.X., (2001) Classificação Mineralógica, Textural e Granulométrica de Detalhe de Minério de Ferro (Pellet Feed) e Suas Implicações Geosiderúrgicas, , III Simpósio Brasileiro de Minério de Ferro. ABM, Ouro Preto
Lowe David, G., Object recognition from local scale-invariant features (1999) Proceedings of the IEEE International Conference on Computer Vision, 2, pp. 1150-1157
Oldenbourg, R., Mei, G., New polarized-light microscope with precision universal compensator (1995) J. Microsc., 180, pp. 140-147
Otsu, N., Threshold selection method from gray-level histograms (1979) IEEE Trans Syst Man Cybern, SMC-9 (1), pp. 62-66
Pirard, E., Lebichot, S., Image analysis of iron oxides under the optical microscope (2004) Applied Mineralogy: Developments in Science and Technology, 1, pp. 153-156. , ICAM-BR, Águas de Lindóia
Pirard, E., Lebichot, S., Krier, W., Particle texture analysis using polarized light imaging and grey level intercepts (2007) International Journal of Mineral Processing, 84 (1-4), pp. 299-309. , DOI 10.1016/j.minpro.2007.03.004, PII S0301751607000671, Special Issue to Honor the Late Professor R. Peter King
Ribeiro M., .R., Vieira C., .B., Investigation on CVRD's iron ores characteristics which have influence on their grinding behavior (2004) 2nd International Meeting on Ironmaking and the 1st International Symposium on Iron Ore, pp. 307-317. , ABM, Vitória
Serra, J., (1982) Image Analysis and Mathematical Morphology, , Academic Press London
Toussaint, G.T., Bibliography on estimation of misclassification (1974) IEEE Trans. Inf. Theory, 20, pp. 472-479
Van Der Maaten, L., (2012) Matlab Toolbox for Dimensionality Reduction [Software], , http://homepage.tudelft.nl/19j49/ Matlab_Toolbox_for_Dimensionality_Reduction.html
Vieira, C.B., Rosiere, C.A., Pena, E.Q., Seshadri, V., Assis, P.S., Avaliação técnica de minérios de ferro para sinterização nas siderúrgicas e minerações brasileiras: Uma análise crítica (2003) Revista Escola de Minas, 56 (2), pp. 97-102
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