| Full text | |
| Author(s): |
Morimitsu, Alexandre
;
Luz Alves, Wonder Alexandre
;
da Silva, Dennis Jose
;
Gobber, Charles Ferreira
;
Hashimoto, Ronaldo Fumio
;
Burgeth, B
;
Kleefeld, A
;
Naegel, B
;
Passat, N
;
Perret, B
Total Authors: 10
|
| Document type: | Journal article |
| Source: | MATHEMATICAL MORPHOLOGY AND ITS APPLICATIONS TO SIGNAL AND IMAGE PROCESSING, ISMM 2019; v. 11564, p. 12-pg., 2019-01-01. |
| Abstract | |
Component-hypertrees are structures that store nodes of multiple component trees built with increasing neighborhoods, meaning they retain the same desirable properties of component trees but also store nodes from multiple scales, at the cost of increasing time and memory consumption for building, storing and processing the structure. In recent years, algorithmic advances resulted in optimization for both building and storing hypertrees. In this paper, we intend to further extend advances in this field, by presenting algorithms for efficient attribute computation and statistical measures that analyze how attribute values vary when nodes are merged in bigger scales. To validate the efficiency of our method, we present complexity and time consumption analyses, as well as a simple application to show the usefulness of the statistical measurements. (AU) | |
| FAPESP's process: | 18/15652-7 - Image segmentation based on shape constraints through the ultimate levelings |
| Grantee: | Wonder Alexandre Luz Alves |
| Support Opportunities: | Regular Research Grants |
| FAPESP's process: | 15/01587-0 - Storage, modeling and analysis of dynamical systems for e-Science applications |
| Grantee: | João Eduardo Ferreira |
| Support Opportunities: | Research Grants - eScience and Data Science Program - Thematic Grants |