Open AccessPotential Fields as an External Force and Algorithmic Improvements in Deformable Models
Author(s) -
Andrés Caro,
Pilar Vega Rodríguez,
E. Cernadas,
M. L. Durán,
Teresa Antequera
Publication year - 2003
Publication title -
elcvia. electronic letters on computer vision and image analysis
Language(s) - English
Resource type - Journals
ISSN - 1577-5097
DOI - 10.5565/rev/elcvia.64
Subject(s) - maxima and minima , computer science , function (biology) , artificial intelligence , domain (mathematical analysis) , energy (signal processing) , image (mathematics) , potential energy , computer vision , selection (genetic algorithm) , field (mathematics) , algorithm , physics , mathematics , classical mechanics , mathematical analysis , quantum mechanics , pure mathematics , evolutionary biology , biology
Deformable Models are extensively used as a Pattern Recognition technique. They are curves defined within an image domain that can be moved under the influence of internal and external forces. Some trade-offs of standard deformable models algorithms are the selection of image energy function (external force), the location of initial snake and the attraction of contour points to local energy minima when the snake is being deformed. This paper proposes a new procedure using potential fields as external forces. In addition, standard Deformable Models algorithm has been enhanced with both this new external force and algorithmic improvements. The performance of the presented approach has been successfully proved to extract muscles from Magnetic Resonance Imaging (MRI) sequences of Iberian ham at different maturation stages in order to calculate their volume change. The main conclusions of this paper are the practical viability of potential fields used as external forces, as well as the validation of the algorithmic improvements developed. The feasibility of applying Computer Vision techniques, in conjunction with MRI, for determining automatically the optimal ripening time of the Iberian ham is a practical conclusion reached with the proposed approach