Topological approach for detecting objects from images

Luis G Nonato; Antonio Castelo; Maria Cristina F. de Oliveira; Mario A. Souza Lizier

doi:10.1117/12.527091

Translator Disclaimer

19 April 2004 Topological approach for detecting objects from images

Luis G Nonato, Antonio Castelo, Maria Cristina F. de Oliveira, Mario A. Souza Lizier

Author Affiliations +

Proceedings Volume 5300, Vision Geometry XII; (2004) https://doi.org/10.1117/12.527091
Event: Electronic Imaging 2004, 2004, San Jose, California, United States

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.

Citation Download Citation

Luis G Nonato, Antonio Castelo, Maria Cristina F. de Oliveira, and Mario A. Souza Lizier "Topological approach for detecting objects from images", Proc. SPIE 5300, Vision Geometry XII, (19 April 2004); https://doi.org/10.1117/12.527091

ACCESS THE FULL ARTICLE