A multiple sensors approach to wood defect detection

This research work reported in this dissertation is the first aimed at creating a vision system utilizes three imaging modalities: a color imaging system, a laser range profiling system and an X-ray imaging system. The objective of in designing this vision system is to detect and identify: (1) surface features such as knots, splits, stains; (2) geometry features such as wane, thin board; and (3) internal features such as voids, knots. The laser range profiling system is used to locate and identify geometry features. The X-ray imaging system is primarily used to detect features such as knots, splits and interior voids. The color imaging system is mainly employed to identify surface features.; In this vision system a number of methodologies are used to improve processing speed and identification accuracy. The images from different sensing modalities are analyzed in a special order to offset the larger amount of image data that comes from the multiple sensors and that must be analyzed. The analysis of laser image is performed first. It is used to find defects that have insufficient thickness. These defects are then removed from consideration in the subsequent analysis of the X-ray image. Removing these defects from consideration in the analysis of the X-ray image not only improves the accuracy of detecting and identifying defects but also reduces the amount of time needed to analyze the X-ray image. Similarly, defect areas such as knot and mineral streak that are found in the analysis of the X-ray image are removed from consideration in the analysis of the color image. A fuzzy logic algorithm---the approaching degree method---is used to assign defect labels. The fuzzy logic approach is used to mimic human behavior in identifying defects in hardwood lumber.; The initial results obtained from this vision system demonstrate the feasibility of locating and identifying all the major defects that occur in hardwood lumber. This was even true during the initial hardware development phase when only images of unsatisfactory quality from a limited lumber of samples were available. The vision system is capable of locating and identifying defects at the production speed of two linear feet per second that is typical in most hardwood secondary manufacturing plants. This vision system software was designed to run on a relative slow computer (200 MHz Pentium processor) with aid of special image processing hardware, i.e., the MORRPH board that was also designed at Virginia Tech. (Abstract shortened by UMI.)...