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

Simon Gazagnes*, Michael H. F. Wilkinson

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)

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 languageEnglish
Article number1940012
Number of pages22
JournalInternational Journal of Pattern Recognition and Artificial Intelligence
Volume33
Issue number11 SI
Early online date7-Mar-2019
DOIs
Publication statusPublished - Oct-2019

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