Segmenting images with gradient-based edge detection using Membrane Computing

Authors:
Daniel DíAz-Pernil;Ainhoa Berciano;Francisco PeñA-Cantillana;Miguel A. GutiéRrez-Naranjo
Affiliations:
CATAM Research Group, Dept. of Applied Mathematics I, University of Seville, Spain;CATAM Research Group, Dept. of Applied Mathematics I, University of Seville, Spain and Department of Didactic of Mathematics and Experimental Sciences, University of the Basque Country, Spain;Research Group on Natural Computing, Dept. of Computer Science and AI, University of Seville, Spain;Research Group on Natural Computing, Dept. of Computer Science and AI, University of Seville, Spain
Venue:
Pattern Recognition Letters
Year:
2013

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Abstract

In this paper, we present a parallel implementation of a new algorithm for segmenting images with gradient-based edge detection by using techniques from Natural Computing. This bio-inspired parallel algorithm has been implemented in a novel device architecture called CUDA(TM)(Compute Unified Device Architecture). The implementation has been designed via tissue P systems on the framework of Membrane Computing. Some examples and experimental results are also presented.