Adaptive Image Segmentation With Distributed Behavior-Based Agents
IEEE Transactions on Pattern Analysis and Machine Intelligence
Genetic Snakes for Color Images Segmentation
Proceedings of the EvoWorkshops on Applications of Evolutionary Computing
A new evolutionary algorithm for image segmentation
EC'05 Proceedings of the 3rd European conference on Applications of Evolutionary Computing
Image segmentation using evolutionary computation
IEEE Transactions on Evolutionary Computation
A cellular coevolutionary algorithm for image segmentation
IEEE Transactions on Image Processing
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This paper describes an image segmentation method based on an evolutionary approach. Unlike other application of evolutionary algorithms to this problem, our method does not require the definition of a global fitness function. Instead a survival probability for each individual guides the progress of the algorithm. 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 various sets of experiments on simulated MR brain images in order to determine the optimal parameter settings. Experimental results on real image are also reported. Images used in this work are color camera photographs of beef meat.