Scanning: what the machines measure and how well

Sawmills are measurement businesses. A log arrives, something or someone decides where it is cut, and the value of the result depends on how well that decision matched what was inside the wood. This course follows the chain scanner, optimiser, machine-learning model and asks at each link what the open literature reports. One rule runs through every lesson: a number is only useful together with its country, its sample and its basis (simulation, laboratory or mill).

External shape: laser and optical scanners

The first generation of log scanners measures only the outside of the log. In general terms, a laser line or structured-light pattern is projected onto the log, cameras record where the line appears shifted, and a diameter profile or 3D surface is computed. (This is general technical background, not a result from one study.)

One open study puts a number on agreement. Shenga and colleagues (BioResources, 2014; the country is not stated on the page) compared a portable 3D phase-shift laser scanner with CT for two logs:

The authors attributed the differences mainly to bark and surface unevenness. Two logs and a portable research scanner are a small basis: read the figures as the scale of agreement, not as a guarantee for any commercial product.

Scanning also moves upstream. A Skogforsk working report (Sweden, June 2026) tested laser scanners and a camera on a harvester to measure sweep, the long curvature of a stem, in standing Scots pine. Handheld mobile laser scanning at 1-5 m height gave an RMSE of 4.4 mm; the harvester-mounted scanner detected about 74% of trees (202 of 288), and the bow-height RMSE was 9.1 mm for the wide-angle scanner and 29 mm for the narrow-angle one. The report gave no percentage value gain.

Internal structure: X-ray and CT

Outside shape only tells part of the story. Knots, resin pockets, rot and density variation sit inside. X-ray and computed tomography (CT) measure attenuation through the log from many angles and reconstruct slices, so knot whorls and decay can be located before the saw. The idea is old: a 1996 USDA Forest Service paper (USA) already used an artificial neural network to label each pixel of a hardwood CT image as knot, split, bark, decay or clear wood. It reported no accuracy number, so it is cited only to show the age of the idea.

A MiCROTEC news story (April 2026, vendor-published) says CT slices have a resolution of around ten millimetres and up to 35 sawing alternatives are simulated per log. These are vendor claims: the page gives no measured recovery gain and no independent audit. Use them to describe what the technology is said to do, never as proof that it does.

Rotation and positioning

A scan is only useful if the decision it feeds can be executed. One executable decision is log rotation: turning the log to a chosen angle before sawing. Fixed rules such as "horns down" or "horns up" can be replaced by a computed best angle. The next lessons show what that is reported to be worth.

Worked example: reading a scanner claim

A supplier says: "Our scanner measures to within 2%." Apply the course rule to the claim.

1. What was measured? Cross-sectional area, diameter, sweep, or something else?
2. Against what reference? In Shenga et al. the reference was CT.
3. On how many logs, which species, with or without bark? Two logs, pine without bark and birch with bark.
4. Which scanner? A portable research scanner is not an in-line production unit.
5. Where and when? Country, line speed, dust.

A claim that cannot answer these five questions is a marketing statement, not evidence.

Checklist for any scanning figure

• Stated quantity and reference method
• Sample size and species
• Research versus production scanner
• Region of the study
• Who published it (vendor, university, mill)

Key points

• External scanners (laser, structured light, phase-shift) measure shape; X-ray and CT see knots and decay inside.
• Shenga et al. reported mean area differences of 2.23% (pine) and 3.73% (birch) against CT, on two logs only.
• Skogforsk harvester-mounted sweep measurement (Sweden) detected about 74% of trees; bow-height RMSE depended on scanner type.
• MiCROTEC statements are vendor claims with no measured gain.
• Always ask: what was measured, against what, on how many logs, in which region.