Binary shape recognition based on an automatic morphological shape decomposition
- 13 January 2003
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 1691-1694 vol.3
- https://doi.org/10.1109/icassp.1989.266773
Abstract
The authors present a technique for translation-invariant binary convex polygon shape recognition based on a morphological shape decomposition. The triangular shape primitives from the decomposition of convex shapes are used as features for shape recognition. The shape primitives are smaller and simpler than the templates of shapes; thus they are more efficient in representing shapes for discrimination. Maximum entropy reduction is used as an optimization criterion for selecting features from among the shape primitives at each node of a decision tree. Experiments on the classification of ten classes of noisy polygon shapes, where five replications per class were used for training and fifty replications per class were used for testing, achieved a recognition rate of 98.80% on the test set.<>Keywords
This publication has 4 references indexed in Scilit:
- Image Analysis Using Mathematical MorphologyPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1987
- Morphological structuring element decompositionComputer Vision, Graphics, and Image Processing, 1986
- Analysis and Design of a Decision Tree Based on Entropy Reduction and Its Application to Large Character Set RecognitionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1984
- Structural Pattern RecognitionPublished by Springer Nature ,1977