This paper describes a new evolutionary algorithm for image segmentation. The evolution involves the colonization of a bidimensional world by a number of populations. The individuals, belonging to different populations, compete to occupy all the available space and adapt to the local environmental characteristics of the world. We present experiments with synthetic images, where we show the efficiency of the proposed method and compare it to other segmentation algorithm, and an application to medical images. Reported results indicate that the segmentation of noise images is effectively improved. Moreover, the proposed method can be applied to a wide variety of images.
A New Evolutionary Algorithm for Image Segmentation / L. Bocchi; L. Ballerini; S. Hassler. - STAMPA. - (2005), pp. 264-273. (Intervento presentato al convegno EvoIASP 2005) [10.1007/b106856].
A New Evolutionary Algorithm for Image Segmentation
BOCCHI, LEONARDO;
2005
Abstract
This paper describes a new evolutionary algorithm for image segmentation. The evolution involves the colonization of a bidimensional world by a number of populations. The individuals, belonging to different populations, compete to occupy all the available space and adapt to the local environmental characteristics of the world. We present experiments with synthetic images, where we show the efficiency of the proposed method and compare it to other segmentation algorithm, and an application to medical images. Reported results indicate that the segmentation of noise images is effectively improved. Moreover, the proposed method can be applied to a wide variety of images.
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