Detecting paper fibre cross sections in microtomy images

Peter Kontschieder*, Michael Donoser, Horst Bischof, Johannes Kritzinger, Wolfgang Bauer

*Corresponding author for this work

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


The goal of this work is the fully-automated detection of cellulose fibre cross sections in microtomy images. A lack of significant appearance information makes edges the only reliable cue for detection. We present a novel and highly discriminative edge fragment descriptor that represents angular relations between fragment points. We train a Random Forest with a plurality of these descriptors including their respective center votes. In such a way, the Random Forest exploits the knowledge about the object centroid for detection using a generalized Hough voting scheme. In the experiments we found that our method is able to robustly detect fibre cross sections in microtomy images and can therefore serve as initialization for successive fibre segmentation or tracking algorithms.

Original languageEnglish
Title of host publicationProceedings for ICPR 2010
Number of pages4
ISBN (Print)9780769541099
Publication statusPublished - 2010
Event20th International Conference on Pattern Recognition: ICPR 2010 - Istanbul, Turkey
Duration: 23 Aug 201026 Aug 2010


Conference20th International Conference on Pattern Recognition
Abbreviated titleICPR'10

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition


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