Cazorla, Miguel, Escolano, Francisco, Gallardo López, Domingo, Rizo, Ramón
Bayesian models for finding and grouping junctions
CAZORLA, M.A., et al. "Bayesian models for finding and grouping junctions". En: Energy Minimization Methods in Computer Vision and Pattern Recognition : Second International Workshop, EMMCVPR’99 York, UK, July 26–29, 1999 Proceedings / Edwin R. Hancock, Marcello Pelillo (Eds.). Berlin : Springer, 1999. (Lecture Notes in Computer Science; 1654). ISBN 3-540-66294-4, pp. 70-82
URI: http://hdl.handle.net/10045/23398
DOI: 10.1007/3-540-48432-9_6
ISSN: 0302-9743 (Print)
ISBN: 3-540-66294-4
Abstract: 
In this paper, we propose two Bayesian methods for detecting and grouping junctions. Our junction detection method evolves from the Kona approach, and it is based on a competitive greedy procedure inspired in the region competition method. Then, junction grouping is accomplished by finding connecting paths between pairs of junctions. Path searching is performed by applying a Bayesian A* algorithm that has been recently proposed. Both methods are efficient and robust, and they are tested with synthetic and real images.
Keywords:Bayesian methods, Junction detection, Junction grouping
Springer Berlin / Heidelberg
info:eu-repo/semantics/conferenceObject