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Optical Engineering

Contour estimation in images using virtual signals
Author(s): Salah Bourennane; Caroline Fossati; Julien Marot
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Paper Abstract

The line-fitting problem has been transposed to the signal-processing framework: Array-processing methods can be applied to virtual signals generated from the image, to estimate straight-line orientations. This paper deals with the estimation of straight and distorted lines in images by fast array-processing methods. Hough transform and snake methods retrieve straight lines and distorted contours, but present limitations. We adapt a fast high-resolution method, the propagator method, to the estimation of multiple distorted contours. For the first time, a method is proposed to cope with the intrinsically limited size of images, which reduces the accuracy of the high-resolution methods due to the low number of signal realizations. Moreover, an extension to images impaired by correlated noise is proposed. For this, an extension of the subspace-based methods to a method based on higher-order statistics is proposed. Distorted contours are assimilated to distorted wavefronts and retrieved with a novel optimization method. The performance of the proposed method is validated on several images.

Paper Details

Date Published: 1 May 2010
PDF: 13 pages
Opt. Eng. 49(5) 057002 doi: 10.1117/1.3421576
Published in: Optical Engineering Volume 49, Issue 5
Show Author Affiliations
Salah Bourennane, Institut Fresnel (France)
Caroline Fossati, Institut Fresnel (France)
Julien Marot, Institut Fresnel (France)

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