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An efficient algorithm to update non-flat and incremental attributes in morphological trees

delete2022-11-01
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PRE
AI
C
Charles Ferreira Gobber
R
Ronaldo F. Hashimoto
W
Wonder Alexandre Luz Alves *
DOI:10.1016/j.patrec.2022.09.005delete
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Abstract

Abstract

En 中文
Attribute Filters are powerful image simplification operators that have very good contour-preservation properties. They can be efficiently computed using morphological trees. The most common strategy to compute attribute filters using morphological trees is based on three steps: (i) tree construction: the tree is built along with its attributes; ( ii ) filtering: we simplify the tree by removing some of its nodes based on some attribute and a filtering rule defined on a threshold value; and ( iii ) image reconstruction: this is the final phase where the tree is converted back to an image leading to an attribute filter. However, after filtering a few attributes in tree may change (we call them as non-flat attributes) and they must be updated, when other attribute filters are applied to the simplified tree again, with either a different or the same threshold value. In this paper we present an efficient algorithm to update non-flat and incremental attributes in morphological trees with low memory consumption and fast computation.(c) 2022 Elsevier B.V. All rights reserved.
Keywords:
Morphological trees
Attribute filters
Incremental Attributes

Journal

Pattern Recognition Letters cover
Pattern Recognition Letters
IF:
3.3
Papers:
7.8K
Citations:
1.6W

Organization

U
Universidade Nove de Julho
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U
universidade de sao paulo
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Citations: 93