A genetic algorithm for image segmentation

The paper describes a new algorithm for image segmentation. It is based on a genetic approach that allow us to consider the segmentation problem as a global optimization problem (GOP). For this purpose, a fitness function, based on the similarity between images, has been defined. The similarity is a...

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Bibliographische Detailangaben
1. Verfasser:	Lo Bosco, G.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Applied sciences Artificial intelligence Computer science control theory systems Deformable models Eigenvalues and eigenfunctions Exact sciences and technology Genetic algorithms Humans Image recognition Image segmentation Layout Pattern recognition. Digital image processing. Computational geometry Shape Surface fitting Visual system
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Beschreibung
Zusammenfassung:	The paper describes a new algorithm for image segmentation. It is based on a genetic approach that allow us to consider the segmentation problem as a global optimization problem (GOP). For this purpose, a fitness function, based on the similarity between images, has been defined. The similarity is a function of both the intensity and the spatial position of pixels. Preliminary results, obtained using real images, show a good performance of the segmentation algorithm.
DOI:	10.1109/ICIAP.2001.957019