| 基于量子遗传算法的二维最大熵图像分割 |
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| 引用本文： | 周露芳,古乐野.基于量子遗传算法的二维最大熵图像分割[J].计算机应用,2005,25(8):1805-1807. |
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| 作者姓名： | 周露芳 古乐野 |
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| 作者单位： | 中国科学院,成都计算机应用研究所,四川,成都,610041;中国科学院,成都计算机应用研究所,四川,成都,610041 |
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| 摘 要： | 图像分割二维最大熵算法存在计算复杂度高的弊端,目前针对这个问题所提出的各类算法效果都不太理想。依据量子遗传算法种群多样性好、收敛速度快的特点,提出了一种基于量子遗传算法的二维最大熵算法,与基于标准遗传算法的二维最大熵算法相比较,取得了更好的实验效果。
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| 关 键 词： | 量子遗传算法 二维最大熵 图像分割 |
| 文章编号： | 1001-9081(2005)08-1805-03 |
2-D maximum entropy method in image segmentation based on genetic quantum algorithm |
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| ZHOU Lu-fang,GU Le-ye.2-D maximum entropy method in image segmentation based on genetic quantum algorithm[J].journal of Computer Applications,2005,25(8):1805-1807. |
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| Authors: | ZHOU Lu-fang GU Le-ye |
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| Affiliation: | Chengdu Institute of Computer Application, Chinese Academy of Sciences, Chengdu Sichuan 610041, China |
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| Abstract: | With high computing complexity, traditional 2-D maximum entropy method is a defective method in image segmentation, although many algorithms have been proposed to bear on this problem. Considering GQAs (Genetic Quantum Algorithm) ability to retain the diversity of population and to converge rapidly, a 2-D maximum entropy method based on GQA was put forward. Compared with 2-D maximum entropy method based on classical genetic algorithm in experiments, this method was proved to perform better. |
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| Keywords: | GQA(Genetic Quantum Algorithm) 2-D maximum entropy image segmentation |
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