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Texture Image Segmentation using Spectral Histogram and Skeleton Extracting

机译:纹理图像分割使用光谱直方图和骨架提取

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This paper presents a texture image segmentation algorithm using spectral histogram and skeleton extracting. No need of selecting seed pixels or specifying or deciding the number of regions is its remarkable characteristic. Based on a local spatial/frequency representation, spectral histogram consists of marginal distributions of responses of a bank of filters and encodes implicitly the local structure of images through the filtering stage and the global appearance through the histogram stage. The similarity between two spectral histograms is measured using χ~2 - statistic. According to the similarity among spectral histograms, the initial binary segmentation image can be obtained. Adopting skeleton extracting algorithm based on mathematical morphology, the final segmentation result can be obtained. Experiments on Brodatz textures give satisfactory results.
机译:本文呈现了一种纹理图像分割算法,使用光谱直方图和骨架提取。不需要选择种子像素或指定或决定区域的数量是其显着的特征。基于局部空间/频率表示,光谱直方图由滤波器银行的响应的边缘分布组成,并且通过滤波阶段通过直方图阶段通过滤波阶段隐式地编码图像的本地结构。使用χ〜2 - 统计来测量两个光谱直方图之间的相似性。根据光谱直方图之间的相似性,可以获得初始二进制分割图像。采用基于数学形态学的骨架提取算法,可以获得最终分割结果。 Brodatz Textures的实验给出了令人满意的结果。

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