Lumber Board Images

University of Oulu and VTT Building Technology

We probably have one of the largest set of color images of lumber boards around. The defects on each board have been located and classified, making the set unique. The images have been captured using the facilities of VTT Building Technology.

The image acquisition has been performed at about 0.5-by-0.3 millimeter resolution using a TVI- Temet Vision Industry 3*12 bit prism based color line-scan camera and Mikrotron Inspecta-2 digital frame grabber. The camera and illuminators are moved by an 8 meter long translation stage and the boards can be imaged from all four sides by turning them 90 degrees between traversals. For the reasons of safety and illumination cost the speed of the camera motion is 0.5 m/s.

The largest objects that can be imaged using the facilities at VTT Building Technology are 0.5m*0.5m*6m. A typical size is around 0.03m*0.5m*5m, so the distance between the illuminators and the board may vary from 0.3m to 0.8m from traversal to traversal. However, because of the real 12 bit dynamic range, the distance variations do not result in a need to adjust the line-scan camera or illumination, greatly facilitating and speeding-up image acquisition.

The pictures below represent two sides of a 3m*0.18m board. The images have been transformed to 3*8 bit GIF-format. Before you click the "thumbnail" images, please, notice that while the size of the GIF-files is approximately 2.4 Mbytes, the uncompressed images take over 11MB each.


For your convenience we also provide the defect files for the images. Many of the defect types are explained on the wood defect page.

Defect file for image 1
Defect file for image 2

If you plan to run tests with the above images, it is a good idea to use 3*8 bit BMP-format versions available from below (approximately 7.5 MB each). The GIF-pictures may have artefacts from format conversion.

Image 1, BMP, gzipped
Image 2, BMP, gzipped

Back to the main lumber inspection page
Olli Silven, University of Oulu
Hannu Kauppinen, University of Oulu
Hannu Rautio, University of Oulu
Olof Sommardahl, VTT Technology