Novel Image Segmentation Methods Based on Improved Ncut Algorithm

摘要：

　　Image segmentation is an important process from image processing to image analysis and scene understanding.Targets of different scales in an image may belong to different classes.Single scale image segmentation methods are prone to over-segmentation or under-segmentation.Combining MeanShfit and Ncut multiscale sampling image segmentation methods,the image is smoothed by MeanShift algorithm and the edges are preserved.Clustering using weights(similarities)between two pixels by Ncut method,this method can be applied to remote sensing image segmentation.In order to solve the problems of high time complexity and long calculation time of Ncut algorithm,firstly,the entropy rate superpixel segmentation algorithm is used to over-segment the image.The algorithm divides the image into a series of compact regions with good regional consistency,Combining Ncut method to solve the weights of similarity between two superpixels to determine the attribution of the region can reduce the segmentation time.Experiments show that this method can use multiscale information for image segmentation effectively.The first method can be applied to remote sensing image segmentation,and the second method can improve the efficiency of Ncut which is suitable for natural scene image segmentation.

关键词： Image segmentation MeanShfit algorithm Graph theory Ncut algorithm Entropy rate superpixel

作者: Dao-cai FU Huai-xin CHEN Yun-zhi YANG Zhou HUANG Chang-yin WANG Bang-mei LI

作者单位: School of Resources and Environment,University of Electronic Science and Technology of China,Chengdu CETC Special Mission Aircraft System Engineering Co.Ltd,Chengdu 611730,China

会议类型: 国际会议

会议名称: 2019 International Conference on Informatics, Control and Robotics 2019信息学、控制和机器人学国际会议(ICICR2019)

会议地点: 上海

会议语种:英文

页码: 225-233

在线出版日期: 2019-06-16（万方平台首次上网日期，不代表论文的发表时间）