Image Segmentation Algorithm Named FSICM Based on Spatial Information

ZHU Suxia; ZU Hongliang; SUN Guanglu

doi:10.15938/j.jhust.2020.04.014

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Image Segmentation Algorithm Named FSICM Based on Spatial Information

更新时间：2026-08-31

- Image Segmentation Algorithm Named FSICM Based on Spatial Information
- Vol. 25, Issue 4, Pages: 101-108(2020)
- 作者机构：
  
  哈尔滨理工大学计算机科学与技术学院,哈尔滨,150080
- 作者简介：
- 基金信息：
- DOI：10.15938/j.jhust.2020.04.014
  CLC： TP3016
- Published：2020
- 稿件说明：
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ZHU Suxia, ZU Hongliang, SUN Guanglu. Image Segmentation Algorithm Named FSICM Based on Spatial Information[J]. 2020, 25(4): 101-108.
DOI：

ZHU Suxia, ZU Hongliang, SUN Guanglu. Image Segmentation Algorithm Named FSICM Based on Spatial Information[J]. 2020, 25(4): 101-108. DOI： 10.15938/j.jhust.2020.04.014.

摘要

针对模糊C均值聚类（FCM）算法存在对噪声和图像中的异常值非常敏感的缺点，本文提出了一种基于空间信息的FCM图像分割算法（Fuzzy spatial information Cmeans clustering

FSICM）。该算法有效的利用图像中的空间信息和待分割图像的灰度信息，提高了对噪声图像的分割精度。首先将得到的空间函数引入到隶属度函数中改变了每个像素点的隶属度权重，以此来抑制噪声。然后，将图像中像素的邻域信息考虑进来，对每个像素进行处理形成线性加权和图像，对新形成的图像的灰度直方图进行聚类。通过对合成图像和真实图像的实验结果表明，FSICM算法对噪声图像的分割精度均在99%以上，对比其他算法，本文提出的算法能够在保持图像重要细节的同时去除噪声，对噪声图像具有鲁棒性。

Abstract

Abstract:In this paper

we present a fuzzy spatialinformation cmeans clustering (FSICM) algorithm for image segmentation byintroducing spatial information

in order to overcome the defects of beingsensitive to noises and outliers in image brought by Fuzzy cmeans clustering (FCM)algorithm The algorithm effectively utilizes the spatial information of theimage and the gray information of the image to be segmented

and improves thesegmentation accuracy of the noisy image Firstly

the spatial function isintroduced into the membership function to change the membership weight of eachpixel so as to suppress the noise Then

the neighborhood information of pixelsin the image is taken into account

each pixel is processed to form a linearweighted image

and the gray histogram of the newly formed image is clusteredExperimental results of both synthetic and real images show that thesegmentation accuracy of FSICM algorithm for noise image is above 99% Comparedwith other algorithms

the algorithm proposed in this paper can remove noisewhile maintaining important details of the image and is robust to noise images

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