| 基于可分离性判据的自适应加权纹理图像分割* |
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| 引用本文： | 关新平,刘冬,唐英干.基于可分离性判据的自适应加权纹理图像分割*[J].计算机应用研究,2005,22(11):233-235. |
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| 作者姓名： | 关新平 刘冬 唐英干 |
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| 作者单位： | (燕山大学 电气工程学院, 河北 秦皇岛 066004) |
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| 基金项目： | 国家自然科学基金资助项目(60174010)；河北省教育厅基金资助项目(2002209) |
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| 摘 要： | 进行自适应加权，以提高可分离性好的特征在分类中所起的作用，使加权后的特征具有更好的分类效果。实验表明，该方法的分割结果比未加权的效果要好。
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| 关 键 词： | 纹理特征 自适应加权 共生矩阵 可分离性 |
| 文章编号： | 1001-3695(2005)11-0233-03 |
| 收稿时间： | 2004-11-02 |
| 修稿时间： | 2005-03-10 |
Adaptive Weight Texture Segmentation Based on Criterion of Separability |
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| GUAN Xin-ping,LIU Dong,TANG Ying-gan.Adaptive Weight Texture Segmentation Based on Criterion of Separability[J].Application Research of Computers,2005,22(11):233-235. |
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| Authors: | GUAN Xin-ping LIU Dong TANG Ying-gan |
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| Affiliation: | (School of Electrical Engineering, Yanshan University, Qinhuangdao Hebei 066004, China) |
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| Abstract: | In this paper, we propose an adaptive weighted method based on feature separability. We use co-occurrence matrix to extract features , then select better features according to criterion of separable, and give different feature adaptive weight to let them more efficient in clustering. Finally, experimental results show that the segmentation has less faults than before. |
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| Keywords: | Texture Feature Adaptive Weight Co-occurrence Matrix Separability |
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