Cookies Policy
X

This site uses cookies. By continuing to browse the site you are agreeing to our use of cookies.

I accept this policy

Find out more here

Detection and Classification of Norway Spruce Compression Wood in Reflected Light by Means of Hyperspectral Image Analysis

No metrics data to plot.
The attempt to load metrics for this article has failed.
The attempt to plot a graph for these metrics has failed.
The full text of this article is not currently available.

Brill’s MyBook program is exclusively available on BrillOnline Books and Journals. Students and scholars affiliated with an institution that has purchased a Brill E-Book on the BrillOnline platform automatically have access to the MyBook option for the title(s) acquired by the Library. Brill MyBook is a print-on-demand paperback copy which is sold at a favorably uniform low price.

Access this article

+ Tax (if applicable)
Add to Favorites
You must be logged in to use this functionality

A methodology has been developed based on reflected light to detect compression wood in stem cross sections of Norway spruce (Picea abies [L.] Karst.). In addition to quantify the spatial distribution of compression wood, the chronological pattern of its formation is recorded by cross linking the pixel classification to the tree ring sequence. An imaging spectrometer is used to record the spectral characteristics in the visible light and near infrared of the cross-sectional surface. Cross-sectional areas are classified by hyperspectral image analysis into severe compression wood, moderate compression wood, normal wood, and background/cracks. The classification is performed by the Spectral Angle Mapper algorithm, which compares the standardized spectrum of each pixel with reference spectra stored in a spectral library. The reference spectra are obtained from selected training areas of the different compression wood severity classes identified by cell characteristics under a light microscope. The tree ring boundaries are located in a grey scale image which shows the spatial information at wavelength 435 nm and the annual radial increment is measured. The classification accuracy is tested by a confusion matrix and cross-analysed with High-Frequency Densitometry.

Loading

Full text loading...

/content/journals/10.1163/22941932-90000203
Loading

Data & Media loading...

http://brill.metastore.ingenta.com/content/journals/10.1163/22941932-90000203
Loading

Article metrics loading...

/content/journals/10.1163/22941932-90000203
2009-01-01
2016-12-04

Sign-in

Can't access your account?
  • Tools

  • Add to Favorites
  • Printable version
  • Email this page
  • Subscribe to ToC alert
  • Get permissions
  • Recommend to your library

    You must fill out fields marked with: *

    Librarian details
    Your details
    Why are you recommending this title?
    Select reason:
     
    IAWA Journal — Recommend this title to your library
  • Export citations
  • Key

  • Full access
  • Open Access
  • Partial/No accessInformation