Identity statement area
Reference TypeConference Proceedings
Last Update2013:
Metadata Last Update2020: administrator
Citation KeyFariasFariMarrClua:2013:PaImSe
TitleParallel image segmentation using reduction-sweeps on multicore processors and GPUs
DateAug. 5-8, 2013
Access Date2020, Dec. 05
Number of Files1
Size940 KiB
Context area
Author1 Farias, Renato
2 Farias, Ricardo
3 Marroquim, Ricardo
4 Clua, Esteban
Affiliation1 Universidade Federal do Rio de Janeiro
2 Universidade Federal do Rio de Janeiro
3 Universidade Federal do Rio de Janeiro
4 Universidade Federal Fluminense
EditorBoyer, Kim
Hirata, Nina
Nedel, Luciana
Silva, Claudio
Conference NameConference on Graphics, Patterns and Images, 26 (SIBGRAPI)
Conference LocationArequipa, Peru
Book TitleProceedings
PublisherIEEE Computer Society
Publisher CityLos Alamitos
History2013-07-08 23:00:49 :: -> administrator ::
2020-02-19 03:09:22 :: administrator -> :: 2013
Content and structure area
Is the master or a copy?is the master
Document Stagecompleted
Content TypeExternal Contribution
Tertiary TypeFull Paper
KeywordsImage segmentation, computer vision, GPU programming, parallel programming.
AbstractIn 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.
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