Pattern recognition using morphological class distribution functions and classification trees

Authors:
Marcin Iwanowski;Michal Swiercz
Affiliations:
Institute of Control and Industrial Electronics, Warsaw University of Technology, Warszawa Poland;Institute of Control and Industrial Electronics, Warsaw University of Technology, Warszawa Poland
Venue:
ISMM'11 Proceedings of the 10th international conference on Mathematical morphology and its applications to image and signal processing
Year:
2011

Citing 5
Cited 1

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On directionality in morphological feature extraction

ICCVG'12 Proceedings of the 2012 international conference on Computer Vision and Graphics

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Abstract

The paper presents an effective and robust method of classifying binary patterns. It starts with classification of foreground pixels of binary image into several spatial classes, which is performed using morphological image processing. By performing this classification with structuring elements of increasing sizes, the spatial class distribution functions are produced. These functions are normalized and sampled in order to obtain feature vectors of constant length that are invariant to pattern translation, rotation and scaling. Such feature vectors are next used to perform tree-based classification.