基于空间聚类和边缘梯度的图像分割算法  

Image Segmentation Algorithm Based on Spatial Clustering and Edge Gradient

作　　者：雍玉洁 顾华[1] YONG Yu-jie;GU Hua(College of Science,Hohai University,Nanjing 211100,China)

机构地区：[1]河海大学理学院,江苏南京211100

出　　处：《计算机与现代化》2021年第2期13-17,共5页Computer and Modernization

基　　金：国家自然科学基金资助项目(61001139)。

摘　　要：提出一种结合空间聚类和边缘梯度信息的图像自动分割算法。在判断超像素颜色及纹理相似性的同时,进一步给出更加精确的分段边缘梯度计算方法,并采用测地距离来刻画超像素之间的相似性,使得分割结果更好地融合边缘不连续性与区域相似性。大量图像分割实验结果表明,该方法能更准确地找出分割边界,提高图像分割的准确性。This paper proposes an automatic image segmentation algorithm which combines spatial clustering and edge gradient information.While evaluating the color and texture similarity of super pixel,a more accurate calculation method of segmented edge gradient is proposed.The geodesic distance is used to describe the similarity between super pixels,so that the segmentation results better integrate edge discontinuity and regional similarity in the image.A large number of experimental results of image segmentation show that this method can find the segmentation boundary more accurately and improve the accuracy of image segmentation.

关 键 词：图像分割 梯度 超像素 测地距离 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]