文章基本信息

标题：An Improved Active Contour Model Based on Local Information
本地全文：下载
作者：Weiqin Chen ; Changjiang Liu ; Bin Pan 等
期刊名称：Open Access Library Journal
印刷版ISSN：2333-9705
电子版ISSN：2333-9721
出版年度：2021
卷号：8
期号：2
页码：1-10
DOI：10.4236/oalib.1107187
语种：English
出版社：Scientific Research Pub
摘要：In view of the problem that the local active contour model is difficult to achieve image segmentation accurately and quickly, an improved image segmentation method based on Local Image Fitting (LIF) is proposed. Firstly, the local median is used as the fitting center of the curve to enhance the robustness of the model to noise. Secondly, a minimized Laplacian of gaussian energy (Log) term is introduced, and the Log operator is used to smooth the image and enhance the edges of the image. Finally, the minimized Log energy term is combined with the LIF, which together drives the curve to the boundary. Experimental results show that the Precision rate, Recall rate and Dice Similarity Coefficient of this model are closest to 1. Compared with other main region-based models, the image segmentation accuracy of this method is significantly higher than that of other algorithms, which improves the anti-noise performance and image segmentation speed.
关键词：Image SegmentationActive ContourLevel SetLocal FittingOptimize Log