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.
|Number of pages||22|
|Journal||International Journal of Pattern Recognition and Artificial Intelligence|
|Issue number||11 SI|
|Early online date||7-Mar-2019|
|Publication status||Published - Oct-2019|