Abstract
Shape recognition is a challenging task when shapes overlap, forming noisy, occluded, partial shapes. This paper uses a genetic algorithm for matching input shapes with model shapes described in terms of features such as line segments and angles (extracted using traditional algorithms). The quality of matching is gauged using a measure derived from attributed shape grammars [12, 13]. Preliminary results, using shapes with about 30 features each, are extremely encouraging.
| Original language | English (US) |
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| Title of host publication | Proceedings of the IEEE Conference on Evolutionary Computation |
| Publisher | IEEE Computer Society |
| Pages | 411-416 |
| Number of pages | 6 |
| State | Published - 1996 |
| Event | Proceedings of the 1996 IEEE International Conference on Evolutionary Computation, ICEC'96 - Nagoya, Jpn Duration: May 20 1996 → May 22 1996 |
Other
| Other | Proceedings of the 1996 IEEE International Conference on Evolutionary Computation, ICEC'96 |
|---|---|
| City | Nagoya, Jpn |
| Period | 5/20/96 → 5/22/96 |
ASJC Scopus subject areas
- General Engineering