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FUZZY-BASED SEGMENTATION OF COLOR NATURAL IMAGES

机译:彩色自然图像的模糊分割

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摘要

This paper presents a segmentation approach for color natural images that performs an edge-preserving smoothing preprocess and a fuzzy-based region growing segmentation. Hue-Chroma-Intensity (HCI) color space is adopted for its perceptual uniformity. The edge-preserving smoothing preprocess is performed to smooth unnecessary details of an original image and obtain stable HCI information before transformation of color space and image segmentation. The proposed segmentation algorithm is performed in two processes: pixel-label assignment and region merging, which builds up fuzzy-based homogeneity measures for any two neighboring pixels, any pixel with its adjacent regions and any two adjacent regions by making a soft fusion of HCI information. We make some experiments to verify the necessity of the preprocess and the effectiveness of the proposed segmentation algorithm for rough segmentation of color natural images.
机译:本文提出了一种彩色自然图像的分割方法,该方法执行了保留边缘的平滑预处理和基于模糊的区域增长分割。色相-色度-强度(HCI)颜色空间因其感知均匀性而被采用。进行边缘保留平滑处理以平滑原始图像的不必要细节并在色彩空间变换和图像分割之前获得稳定的HCI信息。所提出的分割算法在两个过程中执行:像素标签分配和区域合并,该过程通过对HCI进行软融合,为任意两个相邻像素,任何像素及其相邻区域以及任意两个相邻区域建立了基于模糊的均匀性度量信息。我们进行了一些实验,以验证预处理的必要性以及所提出的分割算法对彩色自然图像进行粗分割的有效性。

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