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| 一种纹理图像分割方法--分开-扩张方法 |
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林剑1,2, 鲍光淑2, 肖志强2, 林强2
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1.湖南科技大学,地球空间信息科学研究所,湖南,湘潭,411201;2.中南大学,信息物理工程学院,湖南,长沙,410083
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| 摘要: |
| 针对分开-合并方法分割纹理图像存在的纹理特征不规则性的问题,提出了一种新的基于四分树的分开-扩张的区域分割方法.通过对各类别的不同测量区域的纹理样品进行监督分类,确定分割的初始区域和终止区域,并把样品分类的精度作为各测量区域的纹理特征的权值,根据是否满足一致性属性和区域的性质进行分开或扩张.该方法较好地处理了不同测量区域的纹理特征可信度不一致的问题,扩张的过程可提高分割的精度并避免小区域纹理特征的不稳定.实验结果表明,分开-扩张方法能有效地分割纹理图像,其分割精度优于分开-合并方法. |
| 关键词: 分开-扩张算法 分开-合并算法 纹理分割 模糊纹理光谱 FasART神经网络 |
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| A Segmentation Approach to Texture Images: Split-and-Expand Algorithm |
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LIN Jian,BAO Guang-Shu,XIAO Zhi-Qiang,LIN Qiang
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| Abstract: |
| In order to overcome the problem of irregularity of texture features when using the split-and-merge algorithm to segment texture images, the split-and-expand algorithm, a new quadtree-based texture segmentation approach, is presented in this paper. The initial and final regions to be segmented are determined by supervisedly classifying the texture samples of the different regions to be evaluated, and the precision of classification is treated as the weights of the texture features in the corresponding evaluated regions. Then the operation of spliting or expanding is performed according to whether the properties of consistency are satisfied or not. The method can effectively deal with the problem of inconsistent reliability of texture property in different evaluated regions, and the process of expansion can improve the precision of segmentation and avoid the instability of texture features in smaller regions. The results show that the split-and-expand algorithm can effectively segment texture images, and its precision of classification is superior to that of the split-and-merge algorithm. |
| Key words: split-and-expand algorithm split-and-merge algorithm texture segmentation fuzzy texture spectrum FasART neural network |
