Abstract
The paper describes a new image segmentation algorithm called Combined Genetic segmentation which is based on a genetic algorithm. Here, the segmentation is considered as a clustering of pixels and a similarity function based on spatial and intensity pixel features is used. The proposed methodology starts from the assumption that an image segmentation problem can be treated as a Global Optimization Problem. The results of the image segmentations algorithm has been compared with recent existing techniques. Several experiments, performed on real images, show good performances of our approach compared to other existing methods.
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Di Gesù, V., Bosco, G.L. (2005). Image Segmentation Based on Genetic Algorithms Combination. In: Roli, F., Vitulano, S. (eds) Image Analysis and Processing – ICIAP 2005. ICIAP 2005. Lecture Notes in Computer Science, vol 3617. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11553595_43
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DOI: https://doi.org/10.1007/11553595_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28869-5
Online ISBN: 978-3-540-31866-8
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