Edge-based Segmentation Using Robust Evolutionary Algorithm Applied to Medical Images

Although medical image segmentation is a hard task in image processing, it is possible to reduce its complexity by considering it as an optimization problem. This paper presents a robust evolutionary algorithm based on a cost minimization function to segment and to extract image edges. Since, the go...

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Bibliographic Details
Published in:Journal of signal processing systems 2009, Vol.54 (1-3), p.231-238
Main Author: Mohamed Ben Ali, Yamina
Format: Article
Language:English
Subjects:
Circuits and Systems
Computer Imaging
Electrical Engineering
Engineering
Image Processing and Computer Vision
Pattern Recognition
Pattern Recognition and Graphics
Signal,Image and Speech Processing
Vision
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Summary:Although medical image segmentation is a hard task in image processing, it is possible to reduce its complexity by considering it as an optimization problem. This paper presents a robust evolutionary algorithm based on a cost minimization function to segment and to extract image edges. Since, the goal is to outperform a high edge detection quasi independent from the input problem characteristics, an adaptive detector is considered. As a first step, the main evolutionary algorithm parameters are highlighted based on an adaptive parameterization to overcome convergence problem. In a second stage, the reached optimal setting is applied on medical images to exhibit the quality of the proposed algorithm.
ISSN:1939-8018
1939-8115
DOI:10.1007/s11265-008-0200-z