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Real-time image segmentation on a GPU

AuthorsAbramov, Alexey; Kulvicius, Tomás; Wörgötter, Florentin; Dellen, Babette
KeywordsPattern recognition
Issue Date2010
CitationFacing the Multicore-Challenge: 131-142 (2010)
SeriesLecture Notes in Computer Science 6310
AbstractEfficient segmentation of color images is important for many applications in computer vision. Non-parametric solutions are required in situations where little or no prior knowledge about the data is available. In this paper, we present a novel parallel image segmentation algorithm which segments images in real-time in a non-parametric way. The algorithm finds the equilibrium states of a Potts model in the superparamagnetic phase of the system. Our method maps perfectly onto the Graphics Processing Unit (GPU) architecture and has been implemented using the framework NVIDIA Compute Unified Device Architecture (CUDA). For images of 256 × 320 pixels we obtained a frame rate of 30 Hz that demonstrates the applicability of the algorithm to video-processing tasks in real-time.
DescriptionTrabajo presentado a la Conference for Young Scientists on Facing the Multicore Challenge celebrada en Alemania de 17 al 19 de marzo de 2010.
Publisher version (URL)http://dx.doi.org/10.1007/978-3-642-16233-6_14
Appears in Collections:(IRII) Libros y partes de libros
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