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Proceedings Paper

Topological approach for detecting objects from images
Author(s): Luis G Nonato; Antonio Castelo; Maria Cristina F. de Oliveira; Mario A. Souza Lizier
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Paper Abstract

A novel mathematical framework for topological triangle characterization in 2D meshes is the basis of a system for object detection from images. The system relies on a set of topological operators and their supporting topological data structure to guarantee a precise control of topological changes introduced as a result of inserting and removing triangles from mesh models. The approach enables object models to be created directly from the images without a previous segmentation step. Automatic approaches for modeling objects from images are scarce partly because the process of creating the models typically involves a costly (and generally user-driven) segmentation step to obtain the necessary geometrical information. This issue is critical, for example, in procedures such as surgical planning and physiological studies, or in the simulation of elastic deformation and fluid flow. Our approach is a first step towards automatic mesh generation from images, which may represent a significant progress to a range of applications that handle geometric models. The approach is used to extract robust models from medical images, in order to illustrate how the aggregation of topological information can empower a simple thresholding technique for object detection, making up for the lack of geometrical information in the images.

Paper Details

Date Published: 19 April 2004
PDF: 12 pages
Proc. SPIE 5300, Vision Geometry XII, (19 April 2004); doi: 10.1117/12.527091
Show Author Affiliations
Luis G Nonato, Univ. de Sao Paulo (Brazil)
Antonio Castelo, Univ. de Sao Paulo (Brazil)
Maria Cristina F. de Oliveira, Univ. de Sao Paulo (Brazil)
Mario A. Souza Lizier, Univ. de Sao Paulo (Brazil)


Published in SPIE Proceedings Vol. 5300:
Vision Geometry XII
Longin Jan Latecki; David M. Mount; Angela Y. Wu, Editor(s)

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