Image Segmentation Using Particle Swarm Optimization and a Hybrid Evaluation Function
| Autor: | Chi-Yu Lee, 李啟毓 |
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| Rok vydání: | 2008 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 96 Image segmentation can be treated as a process of dividing an image into some constituent regions and each region is homogeneous. However, no standard can be used to define the level of division of image segmentation, i.e., image segmentation is an ill-posed problem in image processing. In this study, image segmentation using particle swarm optimization (PSO) and a hybrid evaluation function is proposed, in which a visual attention model is employed. The proposed image segmentation approach contains four stages, i.e., color quantization, feature extraction, small region elimination, and region merging using a modified PSO algorithm. Color and texture are used as low-level image features, whereas several properties of the human visual system are used as high-level image semantics. Based on the experimental results obtained in this study, as compared with two comparison methods, the proposed approach will provide the better image segmentation results. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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