Abstract
The standard representations known as component trees, used in morphological connected attribute filtering and multi-scale analysis, are unsuitable for cases in which either the image itself or the tree do not fit in the memory of a single compute node. Recently, a new structure has been developed which consists of a collection of modified component trees, one for each image tile. It has to-date only been applied to fairly simple image filtering based on area. In this paper, we explore other applications of these distributed component forests, in particular to multi-scale analysis such as pattern spectra, and morphological attribute profiles and multi-scale leveling segmentations.
Original language | English |
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Article number | 1940012 |
Number of pages | 22 |
Journal | International Journal of Pattern Recognition and Artificial Intelligence |
Volume | 33 |
Issue number | 11 SI |
Early online date | 7-Mar-2019 |
DOIs | |
Publication status | Published - Oct-2019 |