A system (100A) to track logs in a wood processing chain, includes a database arrangement (102) that includes pre-recorded image of a given log, wherein the given log is associated with log identification information. The system further includes a plurality of imaging devices implemented at a sorting station. The plurality of imaging devices (104) is configured to capture a first set of images from at least a first prespecified oblique angle. The system further includes a data processing arrangement (106) that is configured to: identify the given log at the sorting station; compare the at least one pre-recorded image with the captured first set of images at the sorting station in order to find an optimum image from the compared images for identification of the given log; determine a plurality of physical characteristics; and append the log identification information with the determined physical characteristics of the given log.

An LED matrix lighting device for illuminating a lighting pattern with even intensity. The LED matrix lighting device includes a plurality of LEDs, a collimating lens in front of each LED for collimating light of the LED, and a light refracting element in front of collimating lenses arranged to refract light of at least a first part of the LEDs with a different refraction angle than at least a second part of the LEDs. The disclosure further relates to a machine vision system, a method, and a computer program product.

Near InfraRed NIR technology, including NIR cameras and detectors, is used to accurately determine the strength of the green veneer sheet or other wood product. Based on the determined strength for a given green veneer sheet or other wood product, one or more actions are taken with respect to green veneer sheet or other wood product to ensure the green veneer sheet or other wood product is put the most efficient, effective, and valuable use.

A light 2 for reflected light that emits visible light for reflected light onto a front side of a veneer 6, a light 32 for invisible light that emits near-infrared light for transmitted light onto a back side of the veneer 6, and an image processing device 1 that detects defects of the veneer 6 by analyzing a captured image generated by a line sensor camera 4 are provided. Defects of the veneer 6 are discriminated on the basis of a set of shading and shapes in an infrared-transmitted-light image based on the transmitted light, and colors in a visible-light image based on the reflected light. Consequently, even if a defect has a small color difference from a normal part in the visible-light image, difference of shading between the defective part and the normal part appears in the infrared-transmitted-light image, and a defect that is difficult to detect by seeing only a color difference in a visible-light image can be relatively easily detected.

A computer-implemented method for generating a training dataset for training an artificial neural network configured to use images of lateral faces of a timber board to provide information about structure and/or defects, the method including; a log generation step during which a virtual model of a log is generated; a sawing step of the virtual model to obtain one or more virtual timber boards; a pattern step during which a surface pattern is determined as the intersection between the virtual lateral face and the internal structure and/or defects; a rendering step during which a rendered surface image of the lateral face of the virtual timber board is created; and an input data generation step during which the rendered surface images are used to create one or more item of input data; an output data generation step during which an item of output data is generated; and a population step during which a record is added to the training dataset comprising the item of input data, in combination with the item of output data.

A computer-implemented method for estimating a pith location with regard to a timber board, including: receiving a pixelated actual digital image of each lateral face of at least a longitudinal part of the timber board, extending along a longitudinal axis of the timber board; identifying an input portion in said longitudinal part of the timber board, where the input portion is a portion of the timber board which extends along the longitudinal axis; extracting from each pixelated actual digital image of the longitudinal part of the timber board, an input image representing said input portion, so obtaining four input images representing an appearance of the input portion at each lateral face of the timber board; inputting said four input images into the input layer of an artificial neural network and making the artificial neural network operate; and reading, at an output layer of the artificial neural network, output data defining a location of a pith of a log from which the timber board has been obtained, in a plane perpendicular to the longitudinal axis of the timber board at the input portion.

A method for identifying a log of origin of a first board, comprising an identification step, during which a second board (12) is identified which was obtained from the same log (2) as the first board (11) was obtained from, a studying step, during which identifying features of the second board (12) are identified, and a recognition step during which the log (2) of origin of the first board (11) is recognised, among a plurality of known logs (2) about which saved information is available, and this is done by identifying the log of origin of the second board (12), using the identifying features of the second board (12) itself.

A light 2 for reflected light that emits visible light for reflected light onto a front side of a veneer 6, a light 32 for invisible light that emits near-infrared light for transmitted light onto a back side of the veneer 6, and an image processing device 1 that detects defects of the veneer 6 by analyzing a captured image generated by a line sensor camera 4 are provided. Defects of the veneer 6 are discriminated on the basis of a set of shading and shapes in an infrared-transmitted-light image based on the transmitted light, and colors in a visible-light image based on the reflected light. Consequently, even if a defect has a small color difference from a normal part in the visible-light image, difference of shading between the defective part and the normal part appears in the infrared-transmitted-light image, and a defect that is difficult to detect by seeing only a color difference in a visible-light image can be relatively easily detected.

The present invention relates to a system for repairing a plywood panel. The system comprises an input section and an output section wherein at least one of these comprises a support structure for a stack of the plywood panels. The system may further comprise a detection device for scanning a plywood panel and a repairing device for performing a repair operation for the plywood panel. Moreover, the system may comprise a transport device for transporting a plywood panel from the input section to the output section and a control device for generating a control signal to the repairing device in response to a detection of a defect in the plywood panel on the basis of information obtained with the detection device. The invention also relates to a method implementable by the system.

The wood tracking system for a production line generally has a wood product optimizer; a wood product trimmer downstream from the optimizer in the production line; a conveyor for moving wood products from the optimizer to the trimmer and across a handling area therebetween, the optimizer being configured to scan each of the wood products in a given order and to generate optimization data for each wood product; and a computer vision system positioned proximate the handling area along the production line, the computer vision system having a camera, a processor in communication with the optimizer and with the trimmer and a computer-readable memory for storing the optimization data, the processor being configured to acquire images of the handling area from the camera, the processor being configured to associate the optimization data of a given wood product across each of the images until it arrives at the trimmer.