层次聚类算法和基于图的分割算法相融合的图像分割算法  

Image segmentation algorithm combining hierarchical clustering algorithm and graph-based segmentation algorithm

作　　者：郭昕刚[1] 王佳[1] 程超[1] GUO Xingang;WANG Jia;CHENG Chao(School of Computer Science and Engineering, Changchun University of Technology, Changchun 130012, China)

机构地区：[1]长春工业大学计算机科学与工程学院,吉林长春130012

出　　处：《国防科技大学学报》2022年第3期194-200,共7页Journal of National University of Defense Technology

基　　金：国家自然科学基金资助项目(61903047);吉林省科技厅资助项目(20200401127GX);吉林省发改委资助项目(2019C040-3)。

摘　　要：在基于图的分割(graph-based segmentation,GBS)算法的基础上引入层次聚类算法,构造出一种解决GBS算法欠分割的方法,同时采用多线程并行处理数据的方式,有效改善了传统层次聚类算法的处理速度。该方法首先在RGB彩色空间中使用GBS算法得到图像中每个像素点的初始分割结果,然后提取出每一类区域中的像素值,对其进行层次聚类,得到每一类区域中像素值的类别标签,再根据层次聚类所得到的类别标签和预设的类别范围,修改每个像素点的初始分割结果。根据区域合并准则,生成一个新的分割图。经实验表明,该方法与K-means-SLIC算法和GBS算法等相比,很好地解决了欠分割现象,并产生了分割精度较高的语义分割图。Based on the GBS(graph-based segmentation)algorithm and the hierarchical clustering algorithm,a method to solve the under-segmentation of GBS algorithm was constructed.Meanwhile,the way of multi-threaded parallel processing of data was used to effectively improve the processing speed of the traditional hierarchical clustering algorithm.In the RGB color space,the GBS algorithm was used to obtain the initial segmentation result of each pixel in the image.The pixel value in each type of region was extracted and the hierarchical clustering was carried out to obtain the category label of pixel value in each type of region.According to the category label obtained by hierarchical clustering and the preset category range,the initial segmentation result of each pixel was modified.A new segmentation graph was generated according to the region merging criterion.Experimental results show that compare with the K-means-SLIC algorithm and the GBS algorithm,this method solves the phenomenon of under-segmentation,and produces a semantic segmentation graph with high segmentation accuracy.

关 键 词：图像分割 基于图的分割算法 欠分割 层次聚类 多线程 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]