Share Email Print
cover

Proceedings Paper

A variable parameter parametric snake method
Author(s): A. Marouf; A. Houacine
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

In this paper, we introduce a new approach to parametric snake method by using variable snake parameters. Adopting fixed parameter values for all points of the snake, as usual, constitutes by itself a limitation that leads to poor performances in terms of convergence and tracking properties. A more adapted choice should be the one that allows selection depending on the image region properties as on the contour shape and position. However, such variability is not an easy task in general and a precise method need to be defined to assure contour point dependent tuning at iterations. We were particularly interested in applying this idea to the recently presented parametric method [1]. In the work mentioned, an attraction term is used to improve the convergence of the standard parametric snake without a significant increase in computational load. We show here, that improved performances can ensue from applying variable parameter concepts. For this purpose, the method is first analyzed and then a procedure is developed to assure an automatic variable parameter tuning. The interest of our approach is illustrated through object segmentation results.

Paper Details

Date Published: 8 December 2015
PDF: 5 pages
Proc. SPIE 9875, Eighth International Conference on Machine Vision (ICMV 2015), 98750D (8 December 2015); doi: 10.1117/12.2229474
Show Author Affiliations
A. Marouf, Univ. of Sciences and Technology Houari Boumediène (Algeria)
A. Houacine, Univ. of Sciences and Technology Houari Boumediène (Algeria)


Published in SPIE Proceedings Vol. 9875:
Eighth International Conference on Machine Vision (ICMV 2015)
Antanas Verikas; Petia Radeva; Dmitry Nikolaev, Editor(s)

© SPIE. Terms of Use
Back to Top