dc.creator | Díaz del Río, Fernando | es |
dc.creator | Molina Abril, Helena | es |
dc.creator | Real Jurado, Pedro | es |
dc.creator | Sánchez-Cuevas, Pablo | es |
dc.creator | Ríos Navarro, José Antonio | es |
dc.date.accessioned | 2020-04-25T07:39:00Z | |
dc.date.available | 2020-04-25T07:39:00Z | |
dc.date.issued | 2016 | |
dc.identifier.citation | Díaz del Río, F., Molina Abril, H., Real Jurado, P., Sánchez-Cuevas, P. y Ríos Navarro, J.A. (2016). Parallel Image Processing Using a Pure Topological Framework. En Avances en Arquitectura y Tecnología de Computadores. Jornadas SARTECO (344-350), Cáceres (España): Universidad de Extremadura. | |
dc.identifier.isbn | 9788409121274 | es |
dc.identifier.uri | https://hdl.handle.net/11441/95731 | |
dc.description.abstract | Image processing is a fundamental operation
in many real time applications, where lots of parallelism
can be extracted. Segmenting the image into different
connected components is the most known operations, but
there are many others like extracting the region adjacency
graph (RAG) of these regions, or searching for features
points, being invariant to rotations, scales, brilliant
changes, etc. Most of these algorithms part from the basis
of Tracing-type approaches or scan/raster methods. This
fact necessarily implies a data dependence between the
processing of one pixel and the previous one, which
prevents using a pure parallel approach. In terms of time
complexity, this means that linear order O(N) (N being the
number of pixels) cannot be cut down. In this paper, we
describe a novel approach based on the building of a pure
Topological framework, which allows to implement fully
parallel algorithms. Concerning topological analysis, a first
stage is computed in parallel for every pixel, thus
conveying the local neighboring conditions. Then, they are
extended in a second parallel stage to the necessary global
relations (e.g. to join all the pixels of a connected
component). This combinatorial optimization process can
be seen as the compression of the whole image to just one
pixel. Using this final representation, every region can be
related with the rest, which yields to pure topological
construction of other image operations. Besides, complex
data structures can be avoided: all the processing can be
done using matrixes (with the same indexation as the
original image) and element-wise operations. The time
complexity order of our topological approach for a m×n
pixel image is near O(log(m+n)), under the assumption that
a processing element exists for each pixel. Results for a
multicore processor show very good scalability until the
memory bandwidth bottleneck is reached, both for bigger
images and for much optimized implementations. The
inherent parallelism of our approach points to the
direction that even better results will be obtained in other
less classical computing architectures.1 | es |
dc.description.sponsorship | Ministerio de Economía y Competitividad (España) TEC2012-37868-C04-02 | es |
dc.description.sponsorship | AEI/FEDER (UE) MTM2016-81030-P | es |
dc.description.sponsorship | VPPI of the University of Seville | es |
dc.format | application/pdf | es |
dc.format.extent | 7 p. | es |
dc.language.iso | eng | es |
dc.publisher | Universidad de Extremadura | es |
dc.relation.ispartof | Avances en Arquitectura y Tecnología de Computadores. Jornadas SARTECO (2016), p 344-350 | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Topology | es |
dc.subject | Component-Labeling | es |
dc.subject | Adjacency Tree | es |
dc.subject | Image Processing | es |
dc.subject | Parallelism | es |
dc.title | Parallel Image Processing Using a Pure Topological Framework | es |
dc.type | info:eu-repo/semantics/conferenceObject | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Arquitectura y Tecnología de Computadores | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Matemática Aplicada I (ETSII) | es |
dc.relation.projectID | TEC2012-37868-C04-02 | es |
dc.relation.projectID | MTM2016-81030-P | es |
dc.relation.publisherversion | http://dehesa.unex.es/handle/10662/9626 | es |
dc.contributor.group | Universidad de Sevilla. TEP108: Robótica y Tecnología de Computadores | es |
dc.contributor.group | Universidad de Sevilla. TIC245: Topological Pattern Analysis and Recognition | es |
dc.publication.initialPage | 344 | es |
dc.publication.endPage | 350 | es |
dc.eventtitle | Avances en Arquitectura y Tecnología de Computadores. Jornadas SARTECO | es |
dc.eventinstitution | Cáceres (España) | es |
dc.relation.publicationplace | 9788409121274 | es |