集成高度和彩色纹理特征的影像目标模糊聚类识别方法

Combined Features for Object Extraction Using Fuzzy C-Mean

  • 摘要: 提出一种基于高度和彩色纹理信息的目标识别方法,其目的是提取具有相对高度的地物。由于传统二维纹理分析的方法往往不能有效地提取这类目标,本文把高度、色彩和纹理信息有机地结合起来,提高了识别率。依据影像提取结果,探讨了树林对森林覆盖地区自动空中三角测量选点的负面影响,同时建议采用数据分组的方案来改善森林覆盖地区自动空中三角测量的精度,并用对比实验证明了其有效性。

     

    Abstract: This paper proposes a method for objects extraction based on high and color texture features. The existing methods using two-dimensional texture features are not effective enough for the extraction of the objects which are higher than their surroundings. An architecture is presented that observed points on forest and on non-forest are divided into two different groups in automatic aerial triangulation. The experimental results proves that the method of observed points divided into two different groups can improve the accuracy of automatic aerial triangulation.

     

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