Branches filtering approach for max-tree

Ketut E. Pumama, Michael H.F. Wilkinson, Albert G. Veldhuizen, Peter M.A. van Ooijen, Jaap Lubbers, Tri A. Sardjono, Gijbertus J. Verkerke

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

8 Citations (Scopus)
6 Downloads (Pure)

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.

Original languageEnglish
Title of host publicationProceedings of the Second International Conference on Computer Vision Theory and Applications - IFP/IA
EditorsAlpeshKumar Ranchordas, Helder Araújo, Jordi Vitrià
PublisherSCITEPRESS
Pages328-332
Number of pages5
Volume1
ISBN (Print)978-972-8865-73-3
DOIs
Publication statusPublished - 2007
Externally publishedYes
Event2nd International Conference on Computer Vision Theory and Applications, VISAPP 2007 - Barcelona, Spain
Duration: 8 Mar 200711 Mar 2007
Conference number: 2

Conference

Conference2nd International Conference on Computer Vision Theory and Applications, VISAPP 2007
Abbreviated titleVISAPP 2007
CountrySpain
CityBarcelona
Period8/03/0711/03/07

Keywords

  • Branches filtering
  • Max-tree

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