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基于Curvelet变换的低分辨率煤岩识别方法

伍云霞 张宏

伍云霞, 张宏. 基于Curvelet变换的低分辨率煤岩识别方法[J]. 矿业科学学报, 2017, 2(3): 281-288.
引用本文: 伍云霞, 张宏. 基于Curvelet变换的低分辨率煤岩识别方法[J]. 矿业科学学报, 2017, 2(3): 281-288.
Wu Yunxia, Zhang Hong. Recognition method of low-resolution coal-rock images based on curvelet transform[J]. Journal of Mining Science and Technology, 2017, 2(3): 281-288.
Citation: Wu Yunxia, Zhang Hong. Recognition method of low-resolution coal-rock images based on curvelet transform[J]. Journal of Mining Science and Technology, 2017, 2(3): 281-288.

基于Curvelet变换的低分辨率煤岩识别方法

基金项目: 国家重点研发计划(2016YFC0801800);国家自然科学基金重点资助项目(51134024)
详细信息
    作者简介:

    伍云霞(1967—),女,湖北天门人,副教授,博士,从事矿井监控与通信、数字图像处理与分析和机器视觉等研究.

  • 中图分类号: TD672

Recognition method of low-resolution coal-rock images based on curvelet transform

  • 摘要: 针对小波变换仅能有效表达图像中的点奇异性,难以提取煤岩图像曲线特征的弱点,以及高分辨率煤岩图像计算量大,难以满足煤岩识别实时性要求的问题,提出了一种基于曲波变换的低分辨率煤岩识别方法.该方法通过曲波变换对煤岩图像进行曲波分解,得到各尺度层曲波系数,利用主分量分析进行降维,并将结果分别输入不同k-NN分类器中,对分类结果加权融合,实现煤岩图像的分类识别.实验表明:通过曲波分解提取的特征能够有效地表达煤岩图像的曲线特征,与现有方法相比较,所提出方法具有更高的识别率,平均识别率达95.0%,在煤岩图像分辨率较低情况下也可以获得很高的识别率,满足煤岩识别实时性的要求.
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出版历程
  • 收稿日期:  2016-12-12
  • 刊出日期:  2017-06-30

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