Microtec S.r.l.

Biometic S.r.l.

Sacmi Cooperativa Meccanici Imola Societa' Cooperativa

Enrico Ursella

Federico Giudiceandrea

Enrico Vicario

Giancarlo Zane

Arianna Giudiceandrea

Marco Boschetti

Martin Bacher

Domenico Bambi

Konrad Tschurtschenthaler

Simone Faccini

Thomas Prenn

Davide Barbiero

Davide Boschetto

Nicola Conforto

Federico Guidiceandrea

Method for determining an angular orientation of a log () about one of its longitudinal development axes, comprising a first generation step, during which one or more first digital images are generated of the lateral surface of the log placed in a reference position, using one or more first digital photographs, a second generation step, during which one or more second digital images are generated of the lateral surface () of the log () placed in a second position using the one or more second digital photographs, a step of comparing the one or more second digital images with the one or more first digital images, and a step of determining the angular orientation of the log () in the second position with reference to a reference angular orientation of the log () in the reference position, based on information related to the first digital images and the second digital images for which a match was identified. Also claimed is a device which can implement is programmed to perform the following of the steps described above: the second generation step, the comparison step and the determination step.

Method and device for determining an angular orientation of a log

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

Method for identifying a log of origin of a first board

A processing head () for a forestry machine () is intended to process a tree () having a trunk () with a longitudinal direction (), branches () extending from the trunk () transversely to the longitudinal direction () and knots () extending into the trunk (). The processing head () comprises: a frame () having a seat () for receiving the trunk () of the tree () to be processed; a motorised device for moving the trunk () relative to the seat (), by advancing the trunk () through the seat () along the longitudinal direction () of the trunk (); one or more blades () for cutting the branches () from the trunk () as the trunk () advances; a detection system for detecting positions of the branches () and/or of the knots () on the trunk () as the trunk () advances. Information on the positions of the branches () and/or of the knots () is processed to determine an identification code that is based on said positions and that refers to said trunk () or to a segment obtained from said trunk (). The identification code is comparable against a code determined a posteriori for a specific trunk or for a specific segment of trunk, in order to establish whether the specific trunk or the specific segment of trunk corresponds to said trunk () or to said segment of trunk (). The information on the positions of branches () and/or of knots () can also be used to determine, during a processing of the tree (), one or more positions on the trunk () in which to cut the trunk () perpendicularly or transversely to the longitudinal direction (), which is to say to optimise the truncation of the trunk ().

Processing head for a forestry machine

An industrial tomography apparatus comprising a tomography scan device configured to perform tomography scans of the products placed in the scanning zone and an electronic processing unit programmed to generate a virtual three-dimensional tomography model of a product scanned by the tomography scan device, and to perform a procedure for inspecting industrial products of known type, each comprising a packet or a container. During the inspection procedure the electronic processing unit inspects the virtual three-dimensional tomography model to assess internal features of the product and/or the shape of the product at predetermined zones and determines whether or not those internal features and/or respectively that shape, correspond to a product with intact packet or container. The apparatus implements a corresponding method for checking the integrity of packets or containers of industrial products which have known features.

Industrial tomography apparatus and method for checking the integrity of industrial products

An animal carcass is moved along a movement trajectory which passes through an inspection zone between at least one X-ray emitter and at least one X-ray detector, which are stationary relative to the inspection zone. X-ray detections are performed at successive moments during movement of the animal carcass through the inspection zone, the animal carcass being made to rotate around an axis of rotation which is transversal to lines of propagation of X-rays emitted by the at least one X-ray emitter in the inspection zone, so that what is obtained is a plurality of two-dimensional radiographic images of the animal carcass in different angular positions around the axis of rotation. The two-dimensional radiographic images are processed to determine a cutting pattern and/or a structure of the animal carcass, such as a position of bones, fat and/or lean parts in the animal carcass.

Method and plant for inspecting an animal carcass

An industrial tomography apparatus () comprising a tomography scan device () configured to perform tomography scans of the products () placed in a scanning zone (), and an electronic processing unit operatively connected to the tomography scan device () for receiving from it digital data about the tomography scans performed by the tomography scan device (), and programmed to generate, using that digital data, a virtual three-dimensional tomography model () of a product () scanned by the tomography scan device (), the virtual three-dimensional tomography model () being constituted of a plurality of voxels each of which has its own constant density. In accordance with the method for checking the composition of the products (), the following are performed: a tomography scan step by means of the tomography apparatus () inserted in a production line (), and a step of computerised analysis of the virtual three-dimensional tomography model (), wherein there is assessment of predetermined properties of the primary parts of the product () to which the virtual three-dimensional tomography model () corresponds.

Industrial tomography apparatus and method for checking the composition of industrial products which comprise a plurality of primary parts

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.

Computer-implemented method for training or using a software infrastructure based on machine-learning techniques

A method for recovering a posteriori information about the operation of a plant for automatic classification and sorting of fruit, wherein digital images of a reference piece of fruit previously processed by means of the plant are processed so as to identify its first group of individualizing features, which are then compared with each of a series of second groups of individualizing features each corresponding to a different piece of fruit processed by the plant, in order to establish a match; then, there is extraction from an electronic database of operating information which corresponds to information used or generated by the plant for automatic classification and sorting for classification of the relative processed piece of fruit and/or to information about sorting of the relative piece of fruit processed by the plant for automatic classification and sorting, where in the electronic database the operating information is associated with the second group of individualizing features for which during the comparison step the match with the first group of individualizing features has been established.

Method for recovering a posteriori information about the operation of a plant for automatic classification and sorting of fruit

Computer implemented method for training a software infrastructure based on machine learning techniques and intended for analysis of data obtained from a three-dimensional tomographic inspection of objects of a predetermined type, such as logs, with the aim of determining information about internal characteristics of interest of the self-same objects, wherein, once a training set comprising a plurality of objects of the same predetermined type has been selected, for each object the software infrastructure is supplied with training input data and corresponding training output data, which are processed by the software infrastructure for setting internal processing parameters of the software infrastructure which correlate the training input data with the training output data; where the training input data comprise data obtained from a three-dimensional tomographic inspection of the object, and the training output data comprise information about internal characteristics of interest assessed at internal points of the object, and where the information about the internal characteristics of interest is at least partly assessed at real internal points of the object, previously made accessible by cutting or breaking the object.

Computer implemented methods for training or using a software infrastructure based on machine learning techniques

CT scanner comprising a scanning conveyor () mounted on a supporting structure and configured to move an object () for CT examination forward through a scanning area (), an input conveyor () configured to convey the object until the scanning chamber (), and an output conveyor () configured to convey an object () out of the scanning chamber (), wherein the input conveyor (), the scanning conveyor () and the output conveyor () are configured to move forward the object () placed on a supporting unit () mechanically detached therefore, and wherein the scanning conveyor () is configured to rotate the supporting unit () and the object () on themselves as they travel through the scanning area (). The input conveyor () and the output conveyor () are fitted with shields configured in such a way as to intercept all x-rays emitted from the scanning area () which escape from the scanning chamber () towards the conveyors.

CT scanner and method for performing a CT examination of an object

Apparatus and method for performing computed tomography scans of elongate objects, wherein the object is irradiated with X-rays emitted by a plurality of X-ray emitters which are offset relative to a forward movement direction transversal to the main axis of the object, wherein a rotation device rotates each object about its own main axis of extension while the object is irradiated by one or more beams of X-rays, wherein electronic identifying means estimate the instantaneous position and orientation of the axial portions of the object which are irradiated during the rotation, and wherein an electronic processing and control unit is programmed for combining sets of radiographic data acquired for each axial portion of the object at different detecting moments during the rotation, for processing a three-dimensional tomography reconstruction of the object while taking into account corresponding information about the position and the orientation of each axial portion at each moment.

Apparatus and method for performing a computed tomography scan of an object which has an elongate shape, in particular wooden boards

A method and a related apparatus for performing a tomographic examination of an object () which advances through an examination area (), wherein the examination area () is irradiated with x-rays transversally to a motion trajectory of the object () and the residual intensity of the x-rays which have crossed the object () is repeatedly detected to obtain, for each detection, an electronic two-dimensional pixel map, the two-dimensional maps thus obtained being processed by a computer to obtain a three-dimensional tomographic reconstruction of the object (); wherein, during the advancement, the object () is made or let rotate, at least partly uncontrolled, in such a way that the object () rotates around one or more rotation axes which are transversal both to the motion trajectory and to the propagation directions of the x-rays crossing it; and wherein a computer also determines the spatial position in which the object () is located relative to the one or more emitters () and/or the one or more detectors () at the instant when each two-dimensional map is detected, and factors this in the tomographic reconstruction.

Method and apparatus for performing a tomographic examination of an object

An apparatus for forming compacted powder products. The apparatus includes a powder supply system and a compacting station. An emitter emits an input X-ray beam having a predetermined emission intensity. An output detector detects an output parameter representing an output intensity of the X-ray beam which passes through the powders. A reference detector detects a reference parameter representing the effective intensity of the X-ray beam generated. A control unit is programmed to compensate the output parameter by means of the reference parameter and to generate a control signal representing the density detected and to control the powder supply system by means of the control signal.

Method and apparatus for forming compacted powder products

A tunnel computerised tomographic scanner comprising a rotor (), an X-ray emitter () mounted on the rotor (), an X-ray detector () mounted on the rotor (), on the opposite side of a detecting zone (), the X-ray detector () comprising a scintillator () which has at least one emission face () from which the scintillator () emits light in the visible spectrum when it is struck by X-rays, and a plurality of video cameras () which are positioned in such a way that each of them frames at least one portion of the scintillator (), for acquiring one after another second images, in the visible spectrum, of the respective portion of the scintillator (), wherein, according to the method, at least two separate video cameras () substantially frame each zone of the emission face (), and an electronic processing unit is programmed to combine all of the second images obtained by the video cameras () and to obtain a first image of the emission face (), to be used for the tomographic reconstruction of an object () which is placed in the detecting zone ().

Tunnel computerised tomographic scanner and method for acquiring images from a scintillator of a tunnel computerised tomography scanner

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.

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Mestre, Italy

Enrico Ursella