Defect detection system for lumber

Abstract

A machine vision system that can address a number of board, lineal, cant, and flitch inspection problems by incorporating all the sensors needed to address the surface feature detection problem, the three-dimensional shape detection problem, and the internal feature detection problem. To detect surface features, two color cameras are employed, one for imaging each of the major faces of a board, lineal, cant, or fitch. To address the three-dimensional shape detection problem, a high speed laser profiling device is employed. An x-ray scanning system is employed to detect internal features. The system is able to process material in a species-independent manner by using a histogram-based segmentation procedure for analyzing both the camera imagery and the x-ray imagery; and can detect small defects by removing the effects of large features from the histograms once they have been detected. The system also utilizes redundant information from the set of multiple sensors to improve system accuracy. The volume of data that must be analyzed due the use of three sets of sensors is reduced by ordering the way the data is analyzed. The laser profile data is processed first, followed by the x-ray data and the color imagery. Finally, the system reduces the required volume of data by incorporating a crack/check preserving filter. This filter is implemented in special purpose hardware, and filters the color imagery as it is collected.