Defect detection on hardwood logs using high resolution three dimensional laser scan data

Abstract

The location, type, and severity of external defects on hardwood logs and stems are the primary indicators of overall log quality and value. External defects provide hints about the internal log characteristics. Defect data would improve the sawyer's ability to process logs such that a higher valued product (lumber) is generated. Using a high-resolution laser log scanner, we scanned and digitally photographed 162 red-oak and yellow-poplar logs. By means of a new robust estimator that performs circle fitting, a residual image is extracted from laser scan data that are corrupted by extreme outliers induced by the scanning equipment and loose bark. The residuals provide information to identify defects with height differentiation from the log surface. Combining simple shape definition rules with the height map allows most severe defects to be detected by determining the contour levels of a residual image. In addition, bark texture changes can be examined such that defects not associated with a height change might be detected.