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

A computer-implemented method for training a software infrastructure based on machine-learning techniques to analyse data obtained from a instrumental examination of objects of a predetermined type, where each of the objects has been obtained by splitting a product into smaller pieces, wherein the software infrastructure receives, for each object in a training set, training input data comprising the data obtained from the instrumental examination and training output data comprising information on the characteristics of interest of the training object, wherein the information on the characteristics of interest is, at least in part, information that has been obtained from the results of a tomographic examination of the product from which the training object was obtained, and wherein the software infrastructure processes, through its own training unit, the training input data and the training output data for each training object in order to set internal processing parameters for the software infrastructure which correlate the training input data to the training output data.

The invention relates to a method for illuminating a wood fibre web for deviation detection. The method comprises turning on LEDs of an overhead sidelight that are side-directed towards a first edge of the web for illuminating a first half of width of the web, capturing an image of the first half, turning off the LEDs, turning on LEDs of the overhead sidelight that are side-directed towards a second edge of the web for illuminating a second half of width of the web, capturing an image of the second half, and turning off the LEDs. The invention also relates to an overhead sidelight, a machine vision system, and a lighting system.

A system and method for detecting the origin of wooden planks in a sawmill is provided. The method scans surfaces of processed planks and, with the help of an AI algorithm comprising a deep-learning algorithm, determines the origin of said planks based on analysed parameters of the planks. The parameters used in the analysis are mainly properties of tool marks and the resulting analysis provides tools and equipment used. The deep learning algorithm may be in a self-learning mode or in a supervised training mode.

A disclosed system for providing wood-cultivated ginseng age information includes a background sheet made of paper or plastic, a consumer terminal configured to obtain a wood-cultivated ginseng image of a wood-cultivated ginseng placed on the background sheet by a user, receive the start line of a wood-cultivated ginseng rhizome and the end line of the wood-cultivated ginseng rhizome by the user, calculate a wood-cultivated ginseng rhizome length using the obtained wood-cultivated ginseng image and the obtained start line and end line of the wood-cultivated ginseng rhizome, and transmit the calculated wood-cultivated ginseng rhizome length, and a server configured to previously store wood-cultivated ginseng age information corresponding to a wood-cultivated ginseng rhizome length, search for wood-cultivated ginseng age information corresponding to the wood-cultivated ginseng rhizome length received from the consumer terminal, and transmit the retrieved wood-cultivated ginseng age information to the consumer terminal.

A method for establishing a posteriori a match between a piece of wood and a log from which the piece of wood has been obtained, comprising the following operating steps of performing a tomographic scan of the wooden log, of calculating or selecting a log cutting pattern, of defining, starting with the tomographic information available, one or more virtual individualising characteristics which are linked to the distribution and/or size of physical characteristics of the log inside and/or on the surface of the self-same virtual piece of wood, of saving them in a database, together with information about the identity of the log, of dividing the log into real pieces of wood according to the cutting pattern, of acquiring real information about the distribution and/or size of physical characteristics of the log inside and/or on the surface of a real piece of wood and of defining corresponding real individualising characteristics to be compared with virtual individualising characteristics saved and of identifying an origin of the real piece of wood based on the information about the identity of the log which is saved together with the virtual individualising characteristics which match the real individualising characteristics.

A computer-implemented method for training a software infrastructure based on machine-learning techniques to analyse data obtained from a instrumental examination of objects of a predetermined type, where each of the objects has been obtained by splitting a product into smaller pieces, wherein the software infrastructure receives, for each object in a training set, training input data comprising the data obtained from the instrumental examination and training output data comprising information on the characteristics of interest of the training object, wherein the information on the characteristics of interest is, at least in part, information that has been obtained from the results of a tomographic examination of the product from which the training object was obtained, and wherein the software infrastructure processes, through its own training unit, the training input data and the training output data for each training object in order to set internal processing parameters for the software infrastructure which correlate the training input data to the training output data.

Near InfraRed NIR technology, including NIR cameras and detectors, and machine learning methods and systems, including one or more Machine Learning (ML) based surface irregularity prediction models, are used to accurately identify surface irregularities on a surface of a wood product, such as a veneer sheet or ribbon, and provide irregularity prediction data for the wood product. Based on the irregularity prediction data for a given wood product, one or more actions are taken with respect to wood product or the production process to ensure the wood product is put to the most efficient, effective, and valuable use.

Near InfraRed NIR technology, including NIR cameras and detectors, are used to detect irregularity in the surface of a wood product. Based on the detected irregularities at various locations in a given wood product, one or more actions are taken with respect to a production process used to produce the wood product to ensure the wood product is put to the most efficient, effective, and valuable use.

The invention relates to a computer-implemented method for generating a decorative pattern for decorative panels, such as decorative floor panels, wall panels, or ceiling panels. The invention also relates to a method for manufacturing of decorative panels, by using the aforementioned method according to the invention. The invention further relates to a non-transitory program storage device (NPSD) comprising computer readable instructions executable by one or more processors to perform the method according to the invention. The invention additionally relates to a system, including: one or more processors; and one or more non-transitory program storage devices (NPSDs) including computer readable instructions executable by the one or more processors to perform the method according to the invention. The invention furthermore relates to a decorative panel obtained by applying the manufacturing method according to the invention.