Conţinutul numărului revistei |
Articolul precedent |
Articolul urmator |
1016 6 |
Ultima descărcare din IBN: 2024-01-17 15:25 |
Căutarea după subiecte similare conform CZU |
519.725+004.932 (1) |
Mathematical cybernetics (95) |
Application-oriented computer-based techniques (444) |
SM ISO690:2012 BEJINARIU, Silviu-Ioan, COSTIN, Hariton-Nicolae, ROTARU, Florin, LUCA, Ramona, NITA, Cristina Diana, LAZAR, Camelia. Parallel processing and bio-inspired
computing for biomedical image registration. In: Computer Science Journal of Moldova, 2014, nr. 2(65), pp. 253-277. ISSN 1561-4042. |
EXPORT metadate: Google Scholar Crossref CERIF DataCite Dublin Core |
Computer Science Journal of Moldova | ||||||
Numărul 2(65) / 2014 / ISSN 1561-4042 /ISSNe 2587-4330 | ||||||
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CZU: 519.725+004.932 | ||||||
Pag. 253-277 | ||||||
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Rezumat | ||||||
Image Registration (IR) is an optimization problem computing optimal parameters of a geometric transform used to overlay
one or more source images to a given model by maximizing a similarity measure. In this paper the use of bio-inspired optimization algorithms in image registration is analyzed. Results obtained by means of three di®erent algorithms are compared: Bacterial Foraging Optimization Algorithm (BFOA), Genetic Algorithm(GA) and Clonal Selection Algorithm (CSA). Depending on the images type, the registration may be: area based, which is slow but more precise, and features based, which is faster. In this paper a feature based approach based on the Scale Invariant Feature Transform (SIFT) is proposed. Finally, results obtained using sequential and parallel implementations on multi-core systems for area based and features based image registration are compared. |
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Cuvinte-cheie image registration, clonal selection algorithm, bacterial foraging algorithm, genetic algorithm, parallel computing |
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