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Improving image mining through Geoprocessing

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Abstract

Geoprocessing Information Systems (GIS) deal with structured information concerned some geographical localization. So one uses three-dimensional image representation systems in a huge database, where it is possible to insert many data about some interest domain, say, agriculture, economics, industry, demographics and so on. Images are powerful information sources that can soundly support decision making processes. An image can be seen as a set of elements with spatial localization and color. To interpret an image includes deriving clusters and relations between such elements. This article proposes an integration of Geoprocessing and Image Mining to support image based decisions in several domains such as healthcare.

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Authors and Affiliations

  1. Mestrado em Gestão do Conhecimento e da Tecnologia da Informação, Universidade Católica de Brasíllia, Campus II, SGAN 916 Norte, 70.790-160, Brasília, DF, Brazil

    R. Guadagnin, E. Ferneda & H. Prado

  2. Bacharelado em Fisioterapia, Universidade Católica de Brasília, Campus I, QS 07, Lote 01, EPCT, 71.966-700 Águas Claras, Taguatinga, DF, Brazil

    L. Santana

Authors
  1. R. Guadagnin
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  2. L. Santana
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  3. E. Ferneda
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  4. H. Prado
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Correspondence to R. Guadagnin.

Additional information

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Renato Guadagnin. Mechanical Engineer, Federal University of Rio de Janeiro (1969), Master of Science in Systems Analysis, National Institute for Space Research (1972) and Ph.D., German University of Administrative Sciences, Speyer (1984). He is retired professor from University of Brasilia. He is currently professor at Catholic University of Brasilia. His scientific works concern: information technology management, artificial intelligence, image analysis and visualization.

Edilson Ferneda. Computer Technology Bachelor, Technology Institute of Aeronautics (1979), Master in Computer Science, Federal University of Paraiba (1988), PhD. in Informatics, Montpellier II University (1992). He is currently professor at Catholic University of Brasilia. He has experience in computer science, with emphasis on applied artificial intelligence, knowledge management and knowledge discovery in databases.

Levy Santana. Physiotherapy Bachelor, Paulist State University Julio de Mesquita Filho (1991), Master in Health Sciences, University of Brasilia (1999). He has postgraduate studies in Mechanical Diagnosis and Therapy Method by Mackenzie Method. He is currently physiotherapist at Health State Secretary of Federal District and professor at Catholic University of Brasilia. He has experience in Physiotherapy, mainly on electrotherapy, orthopedics, pressure ulcers, biomechanical and postural stability.

Hércules Antonio do Prado. He holds a Data Processing undergrad (1976) by Federal University of São Carlos, a M.Sc. in Computer Science (1987) by Federal University of Rio de Janeiro, and a D.Sc. in Computer Science by Federal University of Rio Grande do Sul. He joined the Brazilian Enterprise for Agricultural Research in 1984, developing research on computational methods applied to agricultural research. In 1992 he joined the Catholic University of Brasilia as a lecturer in Computer Science and, later, as a researcher in the Graduate Program in Knowledge and Information Technology Management. His research interests includes data mining, knowledge management, organizational learning, and competitive intelligence.

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Guadagnin, R., Santana, L., Ferneda, E. et al. Improving image mining through Geoprocessing. Pattern Recognit. Image Anal. 20, 81–85 (2010). https://doi.org/10.1134/S1054661810010086

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