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基于MATLAB的煤岩图像识别算法的研究

Research of Coal Petrography Image Recognition Algorithm Based on MATLAB
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摘要 煤岩成分识别的目的是识别粘结剂、镜质组和非镜质组。为了能够快速准确地实现煤岩成分识别,采用受限的自动阈值法分割粘结剂,并根据图像每个小窗口中粘结剂成分的比例去除噪声。随后重点介绍了均匀度法识别镜质组,并对这种方法作了理论上的研究和实验上的性能比较。结果表明,均匀度法提取的镜质组识别率和图像信噪比均有了很大的提高,运算速度也大大加快,是综合效果较好的一种方法。 The aim of coal petrography composition recognition is to identify the padding, vitrinite and non- vitrinite. To be able to identify the composition quickly and accurately, a limited auto threshold method is adopted in this paper to identify the padding and eliminate the noise by the ratio of padding in each little window of the image. The PCA and uniformity quality algorithm are used to i- dentify vitrinite in this article, then the theoretical research and practical comparison on these two methods are made. The results show that the identify rate and image SNR of vitrinite that picked up by using the uniformity quality algorithm are greatly improved than that by using the PCA , and the computing speed is also much faster. So the uniformity quality algorithm is a better method with better effect.
出处 《山西电子技术》 2014年第1期95-96,共2页 Shanxi Electronic Technology
关键词 MATLAB 图像处理 阈值法 匀度法 MATLAB image processing threshold method uniformity quality algorithm
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参考文献3

  • 1胡德生,王文韬,刘其真.宝钢数字化自动煤岩分析技术[J].煤炭学报,2003,23(4):412-416.
  • 2Lester E, Allen M, Cloket M. An Automated Image A- nalysis System for Major Maceral Group Analysis in Coals [J]. Fuel, 1994, 73( 11 ) : 1729 - 1734.
  • 3尹文义,刘小除,刘其真,胡德生.用神经网络实现煤岩成分分析[J].计算机工程与应用,2003,39(35):203-205. 被引量:3

二级参考文献1

  • 1袁曾任.人工神经元网络及其应用[M].清华大学出版社,1991.44-48.

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