| Summary: | 碩士 === 國立屏東商業技術學院 === 資訊工程系(原資訊科技系) === 97 === Several methods has so far been proposed in evolutionary computation, that include the particle swarm optimization (PSO), the ant colony optimization (ACO), the genetic algorithm (GA), the simulated annealing (SA). This thesis applies a new evolutionary computation method, the honey bee mating optimization algorithm (HBMO), for the application in multi-level thresholds selection and vector quantization for image compression. The results of HBMO are compared with those of other widely-used algorithm. The experimental results reveal that the application of HBMO is feasible and efficient in the research areas of image processing. Furthermore, it is high potential to further design algorithm in other applications of image processing.
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