Distributed Component Forests in 2-D: Hierarchical Image Representations Suitable for Tera-Scale Images

Gazagnes, S. & Wilkinson, M. H. F., 7-Mar-2019, In : International Journal of Pattern Recognition and Artificial Intelligence.

Research output: Contribution to journalArticleAcademicpeer-review

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 languageEnglish
JournalInternational Journal of Pattern Recognition and Artificial Intelligence
Publication statusE-pub ahead of print - 7-Mar-2019

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