| Texto completo | |
| Autor(es): |
Silva, Dennis J.
;
Miranda, Paulo A. V.
;
Alves, Wonder A. L.
;
Hashimoto, Ronaldo F.
;
Kosinka, Jiri
;
Roerdink, Jos B. T. M.
Número total de Autores: 6
|
| Tipo de documento: | Artigo Científico |
| Fonte: | Journal of Mathematical Imaging and Vision; v. 67, n. 3, p. 23-pg., 2025-06-01. |
| Resumo | |
The distance transform is a crucial technique in binary image processing, assigning the distance to the nearest contour to each foreground pixel. In this extended version of our previous work, we enhance our method for computing the maximum distance transform (DT) value, now utilizing the optimized differential image foresting transform (DIFT) and improved contour extraction processes. These advancements enable more efficient computation of the maximum DT value across all connected components of a grayscale image, significantly reducing computational time by intelligently reusing DIFT trees rooted at contour points (DIFT seeds). Our optimized algorithm now achieves processing speeds that are twice as fast as our previous differential method. The proposed attribute, maximum distance, which measures the thickness of objects within the image, has proven pivotal in different image processing approaches. We showcase this through detailed illustrations of attribute opening, extinction value filters, watershed, and ultimate attribute openings. (AU) | |
| Processo FAPESP: | 18/15652-7 - Segmentação de imagens baseada em restrições de formas por meio dos últimos levelings |
| Beneficiário: | Wonder Alexandre Luz Alves |
| Modalidade de apoio: | Auxílio à Pesquisa - Regular |
| Processo FAPESP: | 15/22308-2 - Representações intermediárias em Ciência Computacional para descoberta de conhecimento |
| Beneficiário: | Roberto Marcondes Cesar Junior |
| Modalidade de apoio: | Auxílio à Pesquisa - Temático |