A Region Growing Segmentation Algorithm for GPUs

Patrick Nigri Happ, Raul Queiroz Feitosa, Cristiana Bentes, Ricardo Farias
Department of Electrical Engineering, Pontifical Catholic University of Rio de Janeiro, R. Marques de Sao Vicente, 225, Gavea, Rio de Janeiro, RJ, Brazil
Internal Research Report, 2013


   title={A Region Growing Segmentation Algorithm for GPUs},

   author={Happ, Patrick Nigri and Feitosa, Raul Queiroz and Bentes, Cristiana and Farias, Ricardo},



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This paper proposes a parallel region growing image segmentation algorithm for Graphics Processing Units (GPU). It is inspired in a sequential algorithm widely used by the Geographic Object Based Image Analysis (GEOBIA) community. Initially, all image pixels are considered as seeds or primitive segments. Fine grained parallel threads assigned to individual pixels merge adjacent segments iteratively following a criterion, which seeks to minimize the average heterogeneity of image segments. Beyond spectral features the merging criterion considers morphological features, which can be efficiently computed in the underlying GPU architecture. Two algorithms using different merging criteria are proposed and tested. An experimental analysis upon five different test images has shown that the parallel algorithm may run more than 19 times faster than its sequential counterpart.
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