Title :
Using fourier-based shape alignment to add geometric prior to snakes
Author :
Charmi, Mohamed Ali ; Ghorbel, Faouzi ; Derrode, Stéphane
Author_Institution :
Lab. CRISTAL, ENSI
Abstract :
In this paper, we present a new algorithm of snakes with geometric prior. A method of shape alignment using Fourier coefficients is introduced to estimate the Euclidean transformation between the evolving snake and a template of the searched object. This allows the definition of a new field of forces making the evolving snake to have a shape similar to the template one. Furthermore, this strategy can be used to manage several possible templates by computing a shape distance to select the best one at each iteration. The new method also solves some well-known limitations of snakes such as evolution in concave boundaries, and enhances the robustness to noise and partially occluded objects. A series of experimental results is presented to illustrate performances.
Keywords :
Fourier transforms; edge detection; shape recognition; Euclidean transformation; Fourier coefficients; Fourier-based shape alignment; geometric prior; shape alignment; shape distance computing; snakes; Active contours; Bayesian methods; Image edge detection; Iterative methods; Level set; Minimization methods; Noise robustness; Noise shaping; Parametric statistics; Shape; Alignment; Euclidean Transform; Snakes; geometric prior;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on
Conference_Location :
Taipei
Print_ISBN :
978-1-4244-2353-8
Electronic_ISBN :
1520-6149
DOI :
10.1109/ICASSP.2009.4959807