海洋科学2011，Vol.35Issue(11)：97-100,4.
基于高斯混合模型的海冰图像非监督聚类分割研究
Sea ice image segmentation with unsupervised clustering based on the Gaussian mixture model
摘要
Abstract
In order to obtain sea ice data from in situ video images, sea ice images were processed with image segmentation technology based on the Gaussian mixture model （GMM）. Image segmentation of the Bohai sea ice with unsupervised clustering was realized by the expectation-maximization （EM） algorithm of GMM and minimum description length （MDL） criterion on the sea ice images for object extraction. The calculation procedures of sea ice image segmentation was described. The results indicate that GMM is effective in sea ice image segmentation and sea ice data extraction. It is concluded that sea ice image recognition, based on image segmentation, is an effective technology to process sea ice image for extraction of data on sea ice type and abundance.关键词
海冰/高斯混和模型/图像分割/非监督聚类Key words
sea ice Gaussian mixture model image segmentation unsupervised clustering分类
海洋科学引用本文复制引用
兰志刚,靳卫卫,朱明亮,于新生,国建凤,周振涛,李凯宝..基于高斯混合模型的海冰图像非监督聚类分割研究[J].海洋科学,2011,35(11):97-100,4.基金项目
中国海洋石油总公司科技发展项目 （）
