Title: Bio-inspired parallel computing of representative geometrical objects of holes of binary 2D-images
Authors: Daniel Díaz-Pernil; Ainhoa Berciano; Francisco Peña-Cantillana; Miguel A. Gutiérrez-Naranjo
Addresses: Department of Applied Mathematics I, CATAM Research Group, University of Seville, Spain ' 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 ' Department of Computer Science and AI, Research Group on Natural Computing, University of Seville, Spain
Abstract: In this paper, we present a bio-inspired parallel implementation of a solution of the problem of looking for the representative geometrical objects of the homology groups in a binary 2D image (extended-HGB2I problem), which is an extended version of a well-known problem in homology theory. In particular, given a binary 2D image, all black connected components and the representative curves of the holes of these components are obtained and labelled. To this aim, a new technique for labelling the connected components of a binary image is presented. In order to compute the solution, the formal framework uses techniques from membrane computing and the implementation has been done in a hardware architecture called compute unified device architecture (CUDA). The computational complexity of the proposed solution is O(m) with respect to the input (image) size m ∼ n². Finally, some examples and applications are also presented.
Keywords: homology groups; computational algebraic topology; membrane computing; tissue-like P systems; compute unified device architecture; CUDA; bio-inspired computation; parallel computing; representative geometrical objects; holes; binary 2D images; component labelling.
International Journal of Bio-Inspired Computation, 2017 Vol.9 No.2, pp.77 - 92
Available online: 21 Mar 2017 *Full-text access for editors Access for subscribers Purchase this article Comment on this article