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Proceedings Paper

Methodology to detect patterns in fluid-flow images
Author(s): Paulo Sergio S. Rodrigues; Arnaldo de Albuquerque Araujo; Marcos Pinotti Barbosa
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Paper Abstract

We are interested in the development of an efficient computational visual system to study dynamic fluids and in this paper we present a methodology to detect patterns in flow-like images. These patterns are called in the Dynamical Systems theory critical points or single points. This method, like other previous methodologies presented in related literature, involves four steps: estimation of flow directions; detection of critical point candidates; matching of critical points; and critical points description according to the Dynamical Systems theory. To achieve the critical point class, node, saddle or center point, we use templates to match the patterns. The last step of the method in necessary only if we wish a numerical representation of the patterns. We ran the method over several real images of some fluid flow classes and present the results.

Paper Details

Date Published: 26 August 1999
PDF: 10 pages
Proc. SPIE 3837, Intelligent Robots and Computer Vision XVIII: Algorithms, Techniques, and Active Vision, (26 August 1999); doi: 10.1117/12.360315
Show Author Affiliations
Paulo Sergio S. Rodrigues, Univ. Federal de Minas Gerais (Brazil)
Arnaldo de Albuquerque Araujo, Univ. Federal de Minas Gerais (Brazil)
Marcos Pinotti Barbosa, Univ. Federal de Minas Gerais (Brazil)

Published in SPIE Proceedings Vol. 3837:
Intelligent Robots and Computer Vision XVIII: Algorithms, Techniques, and Active Vision
David P. Casasent, Editor(s)

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