Logo eprints

On the Relationship between Variational Level Set-Based and SOM-Based Active Contours

Abdelsamea, Mohammed and Gnecco, Giorgio and Gaber, Mohamed Medhat and Elyan, Eyad On the Relationship between Variational Level Set-Based and SOM-Based Active Contours. Computational Intelligence and Neuroscience, 2015 (109029). ISSN 1687-5265 (2015)

[img]
Preview
PDF - Published Version
Available under License Creative Commons Attribution Non-commercial.

Download (2MB) | Preview

Abstract

Most Active Contour Models (ACMs) deal with the image segmentation problem as a functional optimization problem, as they work on dividing an image into several regions by optimizing a suitable functional. Among ACMs, variational level set methods have been used to build an active contour with the aim of modeling arbitrarily complex shapes. Moreover, they can handle also topological changes of the contours. Self-Organizing Maps (SOMs) have attracted the attention of many computer vision scientists, particularly in modeling an active contour based on the idea of utilizing the prototypes (weights) of a SOM to control the evolution of the contour. SOM-based models have been proposed in general with the aim of exploiting the specific ability of SOMs to learn the edge-map information via their topology preservation property and overcoming some drawbacks of other ACMs, such as trapping into local minima of the image energy functional to be minimized in such models. In this survey, we illustrate the main concepts of variational level set-based ACMs, SOM-based ACMs, and their relationship and review in a comprehensive fashion the development of their state-of-the-art models from a machine learning perspective, with a focus on their strengths and weaknesses.

Item Type: Article
Identification Number: 10.1155/2015/109029
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry
T Technology > T Technology (General)
Research Area: Computer Science and Applications
Depositing User: Caterina Tangheroni
Date Deposited: 26 Feb 2016 12:55
Last Modified: 26 Feb 2016 12:55
URI: http://eprints.imtlucca.it/id/eprint/3125

Actions (login required)

Edit Item Edit Item