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Fusion Of Colour And Texture Features In Image Segmentation: An Empirical Study

机译:图像分割中颜色和纹理特征的融合:一项实证研究

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摘要

A study on the fusion of colour and texture features in image segmentation is presented. A series of experiments is conducted to analyse and compare the efficacy of various indexing approaches at every stage of the selection of colour and texture features. The fuzzy c-means clustering algorithm is then applied to combine the selected colour and texture features for image segmentation. The experiments demonstrate that the proposed approach is effective and is able to achieve favourable results in terms of precision and recall when compared with those from the global and local histogram methods.
机译:提出了图像分割中颜色和纹理特征融合的研究。在选择颜色和纹理特征的每个阶段,进行了一系列实验来分析和比较各种索引方法的功效。然后应用模糊c均值聚类算法将所选的颜色和纹理特征进行组合以进行图像分割。实验表明,与全局和局部直方图方法相比,该方法是有效的,并且在精确度和召回率方面能够取得令人满意的结果。

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