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林业资源管理 ›› 2014›› Issue (4): 131-136.doi: 10.13466/j.cnki.lyzygl.2014.04.025

• 技术应用 • 上一篇    下一篇

基于断层图像的木材腐朽程度自动评价方法研究

祁娟1,2, 朱佳1,2, 冯海林1,2, 方益明3, 李光辉1,2   

  1. 1.浙江农林大学 信息工程学院,杭州 311300;
    2.浙江省林业智能检测与信息技术研究重点实验室,杭州 311300;
    3.南京农业大学 工学院,南京 210031
  • 收稿日期:2014-03-06 修回日期:2014-04-14 出版日期:2014-08-28 发布日期:2020-11-23
  • 通讯作者: 冯海林(1980-),男,副教授,博士,主要从事木材无损检测,智能信息处理,无线传感器网络的研究。Email:sealinfeng@gmail.com
  • 作者简介:祁娟(1988-),女,浙江杭州人,在读硕士,主要研究方向为木材无损检测。Email:710350233@qq.com
  • 基金资助:
    国家自然科学基金项目(61272313,61302185);浙江省科技厅公益性项目(2012C21015,2013C31018);浙江省国际合作项目(2013C24026);浙江省教育厅项目(Y201225450)

Evaluation of Decay in Wood Based on Tomographic Images

QI Juan1,2, ZHU Jia1,2, FENG Hailin1,2, FANG Yiming3, LI Guanghui1,2   

  1. 1. School of Information Engineering,Zhejiang A & F University,Hangzhou 311300,China;
    2. Key Lab of Forestery Intelligent Detection and Information Technology of Zhejiang Province,Hangzhou 311300,China;
    3. College of Engineering,Nanjing Agricultural University,Nanjing 210031,China
  • Received:2014-03-06 Revised:2014-04-14 Online:2014-08-28 Published:2020-11-23

摘要: 提出了一种基于断层图像的木材腐朽程度自动评价方法。首先利用Graph Cuts算法对木材断层图像进行分割后,对所得图像进行灰度化处理。然后利用累加直方图技术获取木材断层图像中缺陷部分面积。最后,将测得的木材缺陷面积值与真实值进行比较,从而实现腐朽程度的自动评价。分别采用了含人工模拟腐朽的木材样本和含自然腐朽的木材样本进行实验,结果表明:本文提出的方法具有较高的检测精度,为木材断层图像智能处理和无损检测技术的在线应用提供了新的方法。

关键词: 木材无损检测, 断层图像, 腐朽程度评价, 图像处理

Abstract: This paper presents an automatic evaluation method for the wood decaying degree based on tomographic images.Firstly,the wood tomographic image was partitioned by Graph Cuts,and conversed to grayscale.Then,the cumulative histogram technology was used to obtain the defect part area of the grayscale image.Finally,the measured values were compared with the real values,and the automatic evaluation for the wood decaying degree was implemented.The wood samples containing artificial decay or nature decay were used in our experiments.The experimental results show that the accuracy of the method we proposed is high,and this study provides a new method for the intelligent processing of wood tomographic images and the online application of nondestructive detection technology.

Key words: non-destructive testing of wood, tomographic images, automatic evaluation of decaying degree, image processing

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