Color and texture analysis using emerging parallel architectures
Impacto
Scholar |
Otros documentos de la autoría: Igual, Francisco D.; Mayo, Rafael; Hartley, Timothy; Çatalyürek, Ümit V.; Ruiz, Antonio; Ujaldon, Manuel
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Mostrar el registro completo del ítemcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7036
comunitat-uji-handle3:10234/8620
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http://dx.doi.org/10.1177/1094342010390340 |
Metadatos
Título
Color and texture analysis using emerging parallel architecturesAutoría
Fecha de publicación
2011-11Editor
SAGE PublicationsISSN
1094-3420Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
http://hpc.sagepub.com/content/25/4/404.shortResumen
While image texture is effective for use in pattern-recognition and image-analysis algorithms, textural features are time-consuming to calculate on standard CPUs. Therefore, we present novel implementations of textu ... [+]
While image texture is effective for use in pattern-recognition and image-analysis algorithms, textural features are time-consuming to calculate on standard CPUs. Therefore, we present novel implementations of textural-feature algorithms on graphics processors (GPUs), enabling fast color and texture analysis. Since different textural-feature calculations exhibit diverse characteristics, we focus on using general and algorithm-specific techniques to exploit the inherent parallelism and computational power of a GPU. Common operations required during the textural-feature pipeline range from streaming computations to recursive procedures, from arithmetically intensive transcendental functions to matrix operations. Some of these kernels are well-suited to GPUs, while others require considerable programming effort to fully exploit the memory hierarchy due to their memory-usage patterns. In this paper, different strategies for computing textural features on GPUs are compared with counterpart implementations on multicore CPUs, and experimental results show GPU results reaching a speedup of 500 times for certain operations. [-]
Publicado en
International Journal of High Performance Computing Applications, v. 25, n. 4Derechos de acceso
© The Author(s) 2010
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