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Authors: Ketut E. Purnama 1 ; Michael H. F. Wilkinson 2 ; 4 ; Albert G. Veldhuizen 3 ; Peter M. A. van Ooijen 3 ; Jaap Lubbers 3 and Tri A. Sardjono 3

Affiliations: 1 University Medical Center Groningen, University of Groningen; ITS, Indonesia ; 2 University of Groningen, Netherlands ; 3 no organization, Netherlands ; 4 University Medical Center Groningen, University of Groningen, Netherlands

ISBN: 978-972-8865-73-3

Keyword(s): Branches Filtering, Max-Tree.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Feature Extraction ; Features Extraction ; Image and Video Analysis ; Informatics in Control, Automation and Robotics ; Segmentation and Grouping ; Signal Processing, Sensors, Systems Modeling and Control

Abstract: A new filtering approach called branches filtering is presented. The filtering approach is applied to the Max-Tree representation of an image. Instead of applying filtering criteria to all nodes of the tree, this approach only evaluate the leaf nodes. The expected objects can be found by collecting a number of parent nodes of the selected leaf nodes. The more parent nodes involve the wider the area of the expected objects. The maximum value of the number of parents (PLmax) can be determined by inspecting the output image before having unexpected image. Different images have found have different PLmax values. The branches filtering approach is suitable to extract objects in a noisy image as long as these objects can be recognised from its prominent information such as intensity, shape, or other scalar or vector values. Furthermore, the optimum result can be achieved if the areas which have the prominent information are present in the leaf nodes. The experiments to extract bacteria from noisy image, localizing bony parts in a speckled ultrasound image, and acquiring certain features from a natural image appeared to be feasible give the expected results. The application of the branches filtering approach to a 3D MRA image of human brain to extract the blood vessels gave also the expected image. The results show that the branches filtering can be used as an alternative filtering approach to the original filtering approach of Max-Tree. (More)

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Paper citation in several formats:
E. Purnama K.; H. F. Wilkinson M.; G. Veldhuizen A.; M. A. van Ooijen P.; Lubbers J.; A. Sardjono T.; J. Verkerke G. and (2007). BRANCHES FILTERING APPROACH FOR MAX-TREE.In Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, ISBN 978-972-8865-73-3, pages 328-332. DOI: 10.5220/0002059203280332

@conference{visapp07,
author={Ketut {E. Purnama} and Michael {H. F. Wilkinson} and Albert {G. Veldhuizen} and Peter {M. A. van Ooijen} and Jaap Lubbers and Tri {A. Sardjono} and Gijbertus {J. Verkerke}},
title={BRANCHES FILTERING APPROACH FOR MAX-TREE},
booktitle={Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,},
year={2007},
pages={328-332},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002059203280332},
isbn={978-972-8865-73-3},
}

TY - CONF

JO - Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,
TI - BRANCHES FILTERING APPROACH FOR MAX-TREE
SN - 978-972-8865-73-3
AU - E. Purnama, K.
AU - H. F. Wilkinson, M.
AU - G. Veldhuizen, A.
AU - M. A. van Ooijen, P.
AU - Lubbers, J.
AU - A. Sardjono, T.
AU - J. Verkerke, G.
PY - 2007
SP - 328
EP - 332
DO - 10.5220/0002059203280332

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