Endre søk
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Evolutionary optimisation of a morphological image processor for embedded systems
Högskolan i Borås, Institutionen Ingenjörshögskolan.
2008 (engelsk)Doktoravhandling, monografi (Annet vitenskapelig)
Abstract [en]

The work presented in this thesis concerns the design, development and implementation of two digital components to be used, primarily, in autonomously operating embedded systems, such as mobile robots. The first component is an image coprocessor, for high-speed morphological image processing, and the second is a hardware-based genetic algorithm coprocessor, which provides evolutionary computation functionality for embedded applications. The morphological image coprocessor, the Clutter-II, has been optimised for efficiency of implementation, processing speed and system integration. The architecture employs a compact hardware structure for its implementation of the morphological neighbourhood transformations. The compact structure realises a significantly reduced hardware resource cost. The resources saved by the compact structure can be used to increase parallelism in image processing operations, thereby improving processing speed in a similarly significant manner. The design of the Clutter-II as a coprocessor enables easy-to-use and efficient access to its image processing capabilities from the host system processor and application software. High-speed input-output interfaces, with separated instruction and data buses, provide effective communication with system components external to the Clutter-II. A substantial part of the work presented in this thesis concerns the practical implementation of morphological filters for the Clutter-II, using the compact transformation structure. To derive efficient filter implementations, a genetic algorithm has been developed. The algorithm optimises the filter implementation by minimising the number of operations required for a particular filter. The experience gained from the work on the genetic algorithm inspired the development of the second component, the HERPUC. HERPUC is a hardware-based genetic algorithm processor, which employs a novel hardware implementation of the selection mechanism of the algorithm. This, in combination with a flexible form of recombination operator, has made the HERPUC an efficient hardware implementation of a genetic algorithm. Results indicate that the HERPUC is able to solve the set of test problems, to which it has been applied, using fewer fitness evaluations and a smaller population size, than previous hardware-based genetic algorithm implementations.

sted, utgiver, år, opplag, sider
Chalmers University of Technology, Dep. of Applied Mechanics , 2008.
Serie
Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie, ISSN 0346-718X ; 2759
Emneord [en]
embedded system, machine vision, morphological image processing, genetic algorithm
Emneord [sv]
Energi och material
HSV kategori
Identifikatorer
URN: urn:nbn:se:hb:diva-3479Lokal ID: 2320/3649ISBN: 978-91-7385-078-0 (tryckt)OAI: oai:DiVA.org:hb-3479DiVA, id: diva2:876868
Tilgjengelig fra: 2015-12-04 Laget: 2015-12-04 Sist oppdatert: 2018-01-10

Open Access i DiVA

Fulltekst mangler i DiVA

Personposter BETA

Magnusson, Andreas

Søk i DiVA

Av forfatter/redaktør
Magnusson, Andreas
Av organisasjonen

Søk utenfor DiVA

GoogleGoogle Scholar

isbn
urn-nbn

Altmetric

isbn
urn-nbn
Totalt: 127 treff
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf