首页 | 官方网站   微博 | 高级检索  
     

图像分割技术在金相分析中的应用
引用本文:汤力琨,罗代升,王正勇,龙建忠.图像分割技术在金相分析中的应用[J].理化检验(物理分册),2005,41(5):236-239.
作者姓名:汤力琨  罗代升  王正勇  龙建忠
作者单位:四川大学电子信息学院,成都,610065
摘    要:介绍了常用的图像分割方法及其优缺点和金相图像分析中的图像分割方法。针对金相图像分割中存在的问题,提出了两步分割的图像分割方法。这种方法是先用阈值分割法把目标从背景中分割开来,然后采用数学形态学、打孔、找凹点和连分割线的方法进行粘连分割。与已有的金相图像分割方法相比,这种方法具有较强的强健性、自适应性和非监督性。

关 键 词:金相图像分析  图像分割  数学形态学  阈值分割  粘连分割
文章编号:1001-4012(2005)05-0236-04

IMAGE SEGMENTATION TECHNIQUE APPLIED IN METALLOGRAPHICAL ANALYSIS
TANG Li-kun,LUO Dai-sheng,WANG Zheng-Yong,LONG Jian-zhong.IMAGE SEGMENTATION TECHNIQUE APPLIED IN METALLOGRAPHICAL ANALYSIS[J].Physical Testing and Chemical Analysis Part A:Physical Testing,2005,41(5):236-239.
Authors:TANG Li-kun  LUO Dai-sheng  WANG Zheng-Yong  LONG Jian-zhong
Abstract:In this paper, the traditional methods of image segmentation and their advantages and disadvantages are introduced first. Then the methods of image segmentation for metallographic analysis are introduced. To solve the problems existing in metallographic analysis, a two-step method of image segmentation is proposed. In the method, the objects are segmented first by thresholding. Then the joint or overlapped objects are separated by mathematic morphology, hole opening, concave point finding, and cutting line determination. Compared with the existing segmentation methods in metallographic analysis, this method is robust, adaptive, and unsupervised.
Keywords:Metallographic image analysis  Image segmentation  Mathematic morphology  Thresholding separation  Join separation
本文献已被 CNKI 维普 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司    京ICP备09084417号-23

京公网安备 11010802026262号