中南大学学报（自然科学版）2016，Vol.47Issue(7)：2375-2382,8.DOI:10.11817/j.issn.1672-7207.2016.07.027
基于铸体薄片图像颜色空间与形态学梯度的岩石分类
Rock classification based on features form color space and morphological gradient of rock thin section image
摘要
Abstract
A new high efficiency automatic rock classification method for thin section images of rocks was proposed to solve the problems caused by subjective errors and the difference of capture equipments and conditions. This classification method, whose basic data were from polarizing microscope, was based on original color space and morphology gradient features to build the relationship between these features extracted from images and rock types with SVM. Practical test data set composed of 100 image samples was from Sulige gas field in Ordos basin. The results show that the accuracy of this method reaches 95%, which proves the method is stable and dependable both in theoretical and practical aspects.关键词
岩石图像/分类/颜色空间/形态学梯度/支持向量机Key words
rock images/classification/color space/morphological gradient/SVM分类
天文与地球科学引用本文复制引用
刘烨,程国建,马微,郭超..基于铸体薄片图像颜色空间与形态学梯度的岩石分类[J].中南大学学报（自然科学版）,2016,47(7):2375-2382,8.基金项目
陕西省自然科学基础研究计划项目(2014JQ5193)；西安石油大学青年科技创新基金资助项目(2014BS13)(Project(2014JQ5193) supported by the Natural Science Basic Research Plan in Shaanxi Province of China （2014JQ5193）
Project(2014BS13) supported by the Youth Science and Technology Innovation Fund of Xi'an Shiyou University) （2014BS13）
