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		<doi>10.1109/SIBGRAPI.2013.28</doi>
		<citationkey>FariasFariMarrClua:2013:PaImSe</citationkey>
		<title>Parallel image segmentation using reduction-sweeps on multicore processors and GPUs</title>
		<format>On-line.</format>
		<year>2013</year>
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		<author>Farias, Renato,</author>
		<author>Farias, Ricardo,</author>
		<author>Marroquim, Ricardo,</author>
		<author>Clua, Esteban,</author>
		<affiliation>Universidade Federal do Rio de Janeiro</affiliation>
		<affiliation>Universidade Federal do Rio de Janeiro</affiliation>
		<affiliation>Universidade Federal do Rio de Janeiro</affiliation>
		<affiliation>Universidade Federal Fluminense</affiliation>
		<editor>Boyer, Kim,</editor>
		<editor>Hirata, Nina,</editor>
		<editor>Nedel, Luciana,</editor>
		<editor>Silva, Claudio,</editor>
		<e-mailaddress>renatomdf@gmail.com</e-mailaddress>
		<conferencename>Conference on Graphics, Patterns and Images, 26 (SIBGRAPI)</conferencename>
		<conferencelocation>Arequipa, Peru</conferencelocation>
		<date>5-8 Aug. 2013</date>
		<publisher>IEEE Computer Society</publisher>
		<publisheraddress>Los Alamitos</publisheraddress>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Full Paper</tertiarytype>
		<transferableflag>1</transferableflag>
		<versiontype>finaldraft</versiontype>
		<keywords>Image segmentation, computer vision, GPU programming, parallel programming.</keywords>
		<abstract>In this paper we introduce the Reduction Sweep algorithm, a novel graph-based image segmentation algorithm that is designed for easy parallelization. It is based on a clustering approach focusing on local image characteristics. Each pixel is compared with its neighbors in an implicitly independent manner, and those deemed sufficiently similar according to a color criterion are joined. We achieve fast execution times while still maintaining the visual quality of the results. The algorithm is presented in four different implementations: sequential CPU, parallel CPU, GPU, and hybrid CPU-GPU. We compare the execution times of the four versions with each other and with other closely related image segmentation algorithms.</abstract>
		<language>en</language>
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