Near InfraRed NIR technology, including NIR cameras and detectors, and one or more visual cameras are used to generate superimposed image data representing a visual/NIR composite image of wood product and correlating moisture levels with physical features of the surfaces of the wood product. By analyzing the visual/NIR composite image represented by superimposed image data, moisture pockets near an open physical feature that, absent the presence open physical feature would be a problem, can be identified and ignored. Based on the identified moisture levels at various locations in a given wood product, and the proximity of physical features to the identified moisture locations, one or more actions are taken with respect to wood product to ensure the wood product is put to the most efficient, effective, and valuable use.

The present disclosure provides embodiments of methods, systems, and apparatuses for detecting wet spots on machined surfaces of wood workpieces. Images of laser spots on a workpiece may be processed to determine area and aspect ratio values of the laser spots. Wet spots may be detected on the workpiece based at least on the area and aspect ratio values, and optionally based in part on color image data. A facility may use wet spot detection in grade determination and/or to classify wood pieces as ‘wet’ or ‘dry’ for the determination of appropriate drying conditions.

Provided is a veneer sorting control device including: a sorting condition setting unit 11 that sets sorting conditions for each of a plurality of kinds of defects so as to sort a veneer into a plurality of quality ranks; a defect detection unit 13 that detects the plurality of kinds of defects with respect to each of a plurality of pieces of veneer image data acquired from an image storage unit 100; a quality rank sorting unit 14 that sorts a plurality of the veneers into a plurality of quality ranks in correspondence with the sorting conditions which are set and defect detection states; a first totalization unit 15 that totalizes the number or a number ratio of the veneers in the plurality of quality ranks which are sorted; and a display control unit 17 that displays the totalization result on a screen. The number of the veneers sorted into the plurality of quality ranks can be confirmed by a simulation using the veneer image data stored in the image storage unit 100.

A pole classing system may include an array of three-dimensional (3D) scanners, programmable logic controller equipment, and a computing device. The computing device may control the array of the 3D scanners to generate images of a pole from different directions and positions, generate a first pole dataset comprising dimensions and features of the pole, determine a class for the pole based on the dimensions of the pole and a first set of pole standard parameters, generate a second pole dataset by selecting a partial first pole dataset, and transmit the second pole dataset to the programmable logic controller equipment. The programmable logic controller equipment may process, based on a second set of pole standard parameters, the second pole dataset, the images and the features of the pole to thereby optimize the determined class of the pole and generate an updated class of the pole.

Aspects of the disclosure relate to using computer vision methods for asset evaluation. A computing platform may receive historical images of a plurality of properties and corresponding historical inspection results. Using the historical images and historical inspection results, the computing platform may train a roof waiver model (which may be a computer vision model) to output inspection prediction information directly from an image. The computing platform may receive a new image corresponding to a particular residential property. Using the roof waiver model, the computing platform may analyze the new image to output of a likelihood of passing inspection. The computing platform may send, to a user device and based on the likelihood of passing inspection, inspection information indicating whether or not a physical inspection should be performed and directing the user device to display the inspection information, which may cause the user device to display the inspection information.

The present disclosure describes methods and systems for virtually calibrating geometric sensors with overlapping fields of view. In some embodiments, a geometric sensor may be virtually calibrated by applying a correction value to profile data obtained by the geometric sensor to generate adjusted profile data. The correction factor may be determined based at least in part on X-Y offsets and/or rotational offsets of prior profile data obtained by the geometric sensor relative to corresponding profile data obtained by a reference geometric sensor, and may be recalculated or updated as new sets of profile data are obtained. The adjusted profile data may be used in place of the original profile data in various data processing operations to functionally offset a positional error of the geometric sensor.

Near InfraRed NIR technology, including NIR cameras and detectors, is used to accurately identify surface irregularities on a veneer surface. A grade is then assigned to the veneer based, at least in part, on the detected irregularities. In one embodiment, the veneer is then provided to an improved veneer stacking system that produces more consistently graded veneer stacks and safer veneer stacks, is less expensive to operate, and is far safer than currently available methods and systems for full veneer sheet, veneer strip, and partial veneer sheet stacking.

Near InfraRed NIR technology, including NIR cameras and detectors, is used to accurately identify surface irregularities on a veneer surface. A grade is then assigned to the veneer based, at least in part, on the detected irregularities. In one embodiment, the veneer is then provided to an improved veneer stacking system that produces more consistently graded veneer stacks and safer veneer stacks, is less expensive to operate, and is far safer than currently available methods and systems for full veneer sheet, veneer strip, and partial veneer sheet stacking.

A system that includes a computer processor having a plurality of input data devices, a plurality of output data devices, and a plurality of sensors; and a mechanical assembly integrated with the computer processor to reposition a piece of wood lumber based on software code executing in the computer processor. In some embodiments, the system performs a method that includes eliciting and receiving into the computer processor data parameters from a first human user; obtaining incoming data points about the lumber from the plurality of sensors; processing and storing the data parameters; comparing the incoming data points to the data parameters to obtain comparison results; and, based on the comparison results, (1) rejecting the lumber to a preprogrammed position, (2) feeding the lumber into a saw assembly as positioned, or (3) repositioning the lumber to a more optimal position prior to feeding the lumber to the saw assembly.

A method and apparatus for assembling components of a workpiece. Some embodiments include a work surface; a first digital projector that projects an image of at least some features of the workpiece onto the work surface, wherein the image includes a plurality of line indicators that have visually discernible different markings such as colors or line types; a camera that obtains input images of the work surface and the components of the workpiece; and a first controller configured to receive the input images from the camera and to control the first digital projector to project the first output digital image on the work surface for assembly of the components to form the workpiece, wherein the first controller is further configured to store distortion-correction parameters and to use the stored distortion-correction parameters to adjust the first projected output digital image. In some embodiments, the workpiece is a lumber truss.