arrow
Return

Virtual double-sided image probing: A unifying framework for non-linear grayscale pattern matching

delete2010-10-01
delete10
PRE
AI
C
Cécile Barat *
C
Christophe Ducottet
M
Michel Jourlin
DOI:10.1016/j.patcog.2010.04.020delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
This paper focuses on non-linear pattern matching transforms based on mathematical morphology for gray level image processing. Our contribution is on two fronts. First, we unify the existing and a priori unconnected approaches to this problem by establishing their theoretical links with topology. Setting them within the same context allows to highlight their differences and similarities, and to derive new variants. Second, we develop the concept of virtual double-sided image probing (VDIP), a broad framework for non-linear pattern matching in grayscale images. VDIP extends our work on the multiple object matching using probing (MOMP) transform we previously defined to locate multiple grayscale patterns simultaneously. We show that available methods as well as the topological approach can be generalized within the VDIP framework. They can be formulated as particular variants of a general transform designed for virtual probing. Furthermore, a morphological metric, called SVDIP (single VDIP), is deduced from the VDIP concept. Some results are presented and compared with those obtained with classical methods. (C) 2010 Elsevier Ltd. All rights reserved.
Keywords:
Grayscale pattern matching
Virtual probing
Topology
Mathematical morphology
Compound structuring element
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Pattern Recognition cover
Pattern Recognition
IF:
7.6
Papers:
1.3W
Citations:
4.5W

Organization

C
centre national de la recherche scientifique (cnrs)
Scholars:
24.5W
Papers: 18.2W
Citations: 279