Publication

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

Gazagnes, S. & Wilkinson, M. H. F., Oct-2019, In : International Journal of Pattern Recognition and Artificial Intelligence. 33, 11 SI, 22 p., 1940012.

Research output: Contribution to journalArticleAcademicpeer-review

Copy link to clipboard

Documents

  • Distributed Component Forests in 2-D: HierarchicalImage Representations Suitable for Tera-Scale Images

    Final publisher's version, 2 MB, PDF document

    Request copy

DOI

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
Publication statusPublished - Oct-2019

ID: 78652608