Abstract
In this paper, a reinforcement-learning approach is proposed to color image quantization. Fuzzy rules, which select appropriate parameters for the adaptive clustering algorithm applied to color quantization, are built through the reinforcement learning. Experiment examples are tested to demonstrate the performance of the proposed system.
Original language | English |
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Pages (from-to) | 94-99 |
Number of pages | 6 |
Journal | Proceedings of the IASTED International Conference on Intelligent Systems and Control |
State | Published - 2004 |
Event | Proceedings of the Sixth IASTED International Conference on Intelligent Systems and Control - Honolulu, HI, United States Duration: 23 Aug 2004 → 25 Aug 2004 |
Keywords
- Classifier systems
- Color quantization
- Neuro-fuzzy systems
- Reinforcement learning