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砂岩显微图像分析方法及其工具实现
引用本文:郝慧珍,姜枫,李娜,顾庆.砂岩显微图像分析方法及其工具实现[J].计算机科学,2017,44(11):50-55.
作者姓名:郝慧珍  姜枫  李娜  顾庆
作者单位:南京大学软件学院 南京210023;南京工程学院通信工程学院 南京211167,南京大学计算机科学与技术系 南京210023,南京大学计算机科学与技术系 南京210023,南京大学计算机科学与技术系 南京210023
摘    要:图像分析是研究砂岩薄片的重要手段。研究适用于砂岩薄片的图像分析的方法并进行工具实现,在岩石学研究、油气勘探等方面具有重要意义。文中设计开发了砂岩显微图像分析软件系统。首先,提出基于超像素分割和聚类的图像分割方法来分割砂岩薄片显微图像,形成只具有单一矿物成分的超像素;然后,以矿物显微图像作为训练数据,提取颜色和局部等特征参数来训练分类器分类超像素;最后,合并相邻超像素从而形成完整的矿物颗粒,并标定其类别成分。在对方法进行研究的基础上,进行软件设计实现,对砂岩薄片显微图像中的矿物组分和组构特征进行分析。对一些采自西藏的典型砂岩薄片显微图像的分析表明,该方法具有良好的实用价值,但还需要进一步完善和优化。

关 键 词:砂岩  显微图像  超像素  图像分割  分类  标记
收稿时间:2016/10/11 0:00:00
修稿时间:2016/12/5 0:00:00

Sandstone Microscopic Image Analysis Method and Tool Implementation
HAO Hui-zhen,JIANG Feng,LI Na and GU Qing.Sandstone Microscopic Image Analysis Method and Tool Implementation[J].Computer Science,2017,44(11):50-55.
Authors:HAO Hui-zhen  JIANG Feng  LI Na and GU Qing
Affiliation:Software Institute,Nanjing University,Nanjing 210023,China;School of Communication Engineering,Nanjing Institute of Technology,Nanjing 211167,China,Department of Computer Science and Technology,Nanjing University,Nanjing 210023,China,Department of Computer Science and Technology,Nanjing University,Nanjing 210023,China and Department of Computer Science and Technology,Nanjing University,Nanjing 210023,China
Abstract:Image analysis is an important method for studying sandstone.The research to develop methods which are suitable for sandstone microscopic image analysis and its implementation are valuable for both studying sandstone petrology and oil-gas exploration.This work developed a software system for sandstone microscopic image analysis.Firstly,superpixel segmentation method SLIC is adapted to segment microscopic images of sandstone which forms superpi-xels with only one mineral ingredient.Secondly,as the training data,the color and local features are extracted from micro-mineral images,and are used to train classifier to classify superpixels.Lastly,those adjective superpixels are merged to a whole mineral grain which is labeled with its category as a result.Based on this method,a set of tools were designed to perform mineral composition and texture analysis on the sandstone microscopic images.The analysis on microscopic images of sandstones from Tibet verified this method to be practical and useful.However,this developed software tool need to be further improved and optimized.
Keywords:Sandstone  Microscopic image  Superpixel  Image segmentation  Classification  Annotation
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