[1]陈勇平,王正,常亮,等.基于3种图像处理方法的杨树木材表面孔隙度比较[J].福建林学院学报,2013,33(04):381-384.
 CHEN Yong-ping,WANG Zheng,CHANG Liang,et al.Measurement of surface porosity of poplar wood species based on three image processing methods[J].Journal of Fujian College of Forestry,2013,33(04):381-384.
点击复制

基于3种图像处理方法的杨树木材表面孔隙度比较()
分享到:

《福建林学院学报》[ISSN:2096-0018/CN:35-1327/S]

卷:
33
期数:
2013年04期
页码:
381-384
栏目:
出版日期:
2013-10-15

文章信息/Info

Title:
Measurement of surface porosity of poplar wood species based
on three image processing methods
文章编号:
1001-389X(2013)04-0381-04
作者:
陈勇平12 王正1 常亮1 方露1
(1.中国林业科学研究院林业新技术研究所,北京 100091;
2.中国林业科学研究院木材工业研究所,北京 100091)
Author(s):
CHEN Yong-ping12 WANG Zheng1 CHANG Liang1 FANG Lu1
(1.Research Institute for Forestry New Technology, Chinese Academy of Forestry, Beijing 100091, China;
2.Research Institute of Wood Industry, Chinese Academy of Forestry, Beijing 100091, China)
关键词:
图像处理 色域 表面孔隙度 管孔 杨树
Keywords:
image processing color gamut surface porosity vessel pore poplar
分类号:
S718.3
文献标志码:
A
摘要:
以转基因欧洲黑杨、北抗杨、转基因741杨和107杨为研究对象,通过图像处理后的色域分析,测量了木材表面孔隙度,并与Image-Pro Plus图像分析法和直线测量法进行比较。结果表明,Image-Pro Plus图像分析法可以直观获得木材横切面上管孔大小数值,但难以测量木材表面孔隙度;直线法虽然简化了测量工作,但仍旧耗费时间;基于图像处理的色域测定法在图片导入后可以即时获取木材表面孔隙度信息。色域测定法和直线测量法结果相当,4种杨树木材表面孔隙度大小依次为转基因欧洲黑杨>北抗杨>转基因741杨>107杨,其中直线测量法结果为 75.91%、72.88%、70.73%、69.98%,色域测定法结果为 70.61%、68.56%、65.56%、65.26%,Image-Pro Plus图像分析法测定管孔所占比率分别为 20.76%、20.92%、22.64%、26.81%。
Abstract:
The wood surface porosity of poplar species [Populus nigra ‘Shiji’ (GMO), P.deltoides cl.‘Beikang’, P.alba×(P.davidiana+P.simonii)×P.tomentosa and P.euramericana cv.‘Neva’] was measured using the so-called color gamut displaying method, which was also compared with the Image-Pro Plus analysis and the straight-line method. The results showed that the pore size of vessels on wood cross-section could be easily calculated based on the Image-Pro Plus analysis software, but the measurement of surface porosity was problematic. The straight-line method simplified the analysis procedure whereas still being time-consuming. By contrast, the color gamut displaying method could obtain wood surface porosity quickly upon importing pictures to the software. The wood surface porosity of different poplar species measured based on color gamut displaying method was comparable to the result of straight-line method, and both methods indicated the sequence as follows: P.nigra ‘Shiji’ (GMO)>P.deltoides cl.‘Beikang’>P.alba×(P.davidiana+P.simonii)×P.tomentosa>P.euramericana cv.‘Neva’. The results of strait-line method are 75.91%, 72.88%, 70.73%, 69.98%, the results of color gamut displaying method are 70.61%, 68.56%, 65.56%, 65.26%, the measured vessel pore ratios based on Image-Pro Plus method are 20.76%, 20.92%, 22.64%, 26.81%.

参考文献/References:

[1] McMillin, Charles W. Application of automatic image analysis to wood science[J]. Wood Science, 1982,14(3):97-105.
[2] Jordan B D. A simple image analysis procedure for fiber wall thickness[J]. Pulp and Paper Science, 1988,14(2):44-45.
[3] 王秀华,刘镇波,刘一星.木材横切面显微图像特征参数的主成分分析[J].东北林业大学学报,2005, 33(5):30-37.
[4] 任宁,于海鹏,刘一星.应用数字图象处理技术测量木材显微构造特征参数[C]∥中国林学会木材科学分会第十次学术研讨会论文集.南宁:广西大学出版社,2005:576-581.
[5] Chen G S, Zhao P. Dynamic wood slice recognition using image blur information[J]. Sensors and Actuators A: Physical, 2012,176:27-33.
[6] Van D B, Van A J, Stevens M. Image processing as a tool for assessment and analysis of blue stain discoloration of coated wood[J]. International Biodeterioration & Biodegradation, 2005,56(3):178-187.
[7] Funck J W, Zhong Y, Butler D A, et al. Image segmentation algorithms applied to wood defect detection[J]. Computers and Electronics in Agriculture, 2003,41(1-3):157-179.
[8] Mallik A, Tarrío J. Classification of wood micrographs by image segmentation[J]. Chemo Metrics and Intelligent Laboratory Systems, 2011,107(2):351-362.
[9] Pan S, Kudo M. Segmentation of pores in wood microscopic images based on mathematical morphology with a variable structuring element[J]. Computers and Electronics in Agriculture, 2011,75(2):250-260.
[10] Pham D T, Alcock R J. Segmentation of birch wood board images[C]∥Proceedings International Workshop on Image and Signal Processing, 1996:637-640.
[11] 成俊卿.木材学[M].北京:中国林业出版社,1985:469-450.

备注/Memo

备注/Memo:
基金项目:中国林业科学研究院林业新技术研究所基本科研业务费专项基金项目“基于图像识别的装饰单板外观分等技术研究”(CAFINT2013C06);国家林业公益性行业科研专项经费重大项目“杨树产业资源材培育及新产品开发关键技术研究”(201004004)。
更新日期/Last Update: 2015-03-12