Abstract
A new method for the selection of the optimal structuring element for shape description and matching based on the morphological signature transform (MST) is presented in this paper. For a given class of shapes the optimal structuring element for MST method is selected by means of a genetic algorithm. The optimization criteria is formulated to enable a robust shape matching. Experiments have been performed on a class of model shapes. The proposed optimal shape description method is applied to the problem of shape matching which evolves in many object recognition applications. Here, an unknown object is matched to a set of known objects in order to classify it into one of finite number of classes. Experimental results are presented and discussed.
Original language | English (US) |
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Pages (from-to) | 571-579 |
Number of pages | 9 |
Journal | Pattern Recognition |
Volume | 28 |
Issue number | 4 |
DOIs | |
State | Published - Apr 1995 |
Externally published | Yes |
All Science Journal Classification (ASJC) codes
- Software
- Signal Processing
- Computer Vision and Pattern Recognition
- Artificial Intelligence
Keywords
- Genetic algorithms
- Mathematical morphology
- Multiresolution pyramid
- Shape description
- Shape matching Multiscale representation