计算机应用与软件2025，Vol.42Issue(5)：209-216,8.DOI:10.3969/j.issn.1000-386x.2025.05.029
基于高斯混合模型的尿沉渣图像有形成分分割
FORMED ELEMENTS SEGMENTATION OF URINE SEDIMENT IMAGE BASED ON GAUSSIAN MIXTURE MODEL
摘要
Abstract
In order to solve the problems of urinary sediment images with various kinds,low contrast and include blurred borders,a formed elements segmentation method of urine sediment image based on Gaussian mixture model(GMM)is proposed.The edge intensity and area density were fused by using the constructed spatial constraint relationship to extract the effective area of the image.The core region enhancement method was used to enhance the effective area of texture features and construct the complete observation data.The spatial correlation of adjacent pixels was introduced into the local region to constrain the Gaussian mixture model.The conditional iterative algorithm was used to optimize the maximum posteriori probability of the label field to realize image segmentation.The experimental results show that the proposed method could successfully improve the accuracy and completeness of image segmentation.关键词
高斯混合模型/图像分割/尿沉渣图像Key words
Gaussian mixture model/Image segmentation/Image of urine sediment分类
计算机与自动化引用本文复制引用
常永鑫,黄雪东,马婷,张文瑞..基于高斯混合模型的尿沉渣图像有形成分分割[J].计算机应用与软件,2025,42(5):209-216,8.基金项目
国家自然科学基金青年科学基金项目(51905457). （51905457）
