Advanced Vision Technology (a.v.t.) Ltd.

Advanced Vision Technologies (a.v.t.) Ltd.

Advaced Vision Technology (a.v.t.) Ltd.

Advanced Vision Technology Ltd.

Barry Ben Ezra

Chanan Gazala

Dan Zamir

Gilad Golan

Alan Then

Brian Gamm

Leon Kanelovitch

Tsachi Mazliach

Dani Zamir

A method and system for implementation of quality control includes a machine vision system for capturing images of instances of a product, and a computer system including computer memory containing machine-readable instructions executable by a processor. The processor evaluates the quality control images for a plurality of potential quality defects in the product and generates a defect alert associated with a captured image in which at least one potential quality defect is identified. Information about each defect alert is stored in a database log file in the computer memory. A neural network machine learning algorithm processes the database log file by, in a learning phase, receiving human-initiated input accepting or rejecting each defect alert and storing the human-initiated input in the log file, and, in an automated phase, automatically accepting or rejecting at least some defect alerts without performing the step of receiving human initiated input.

Method and process for automated auditing of inline quality inspection

A method for printing a plurality of instances of a printed image on a substrate includes providing one or more units of substrate for receiving the plurality of instances, providing information documenting a plurality of measured characteristics for each unit, developing a printing plan based at least in part upon the information documenting the plurality of measured characteristics, and printing the plurality of instances in accordance with the printing plan. The printing plan includes one or more of: a screen having one or more characteristics tailored at least in part to at least one color value based upon the measured characteristics, a mapping of color specifications for the plurality of instances of the printed image indexed to location on the substrate unit or partial unit, and a mapping of one or more no-print locations indexed to location on the substrate unit or partial unit.

Method for developing a printing plan

A combined imaging and spectral measurement line-scan imaging sensor includes a plurality of pixel lines. Each pixel line includes a plurality of pixels. At least one of the pixel lines is an imaging line designated for acquiring at least one image of an object and other of the pixel lines are spectral measurement lines designated for acquiring a spectral measurement of light received from the object. Each imaging line is associated with a single respective spectral response within a spectral range. Each pixel in each spectral measurement line is associated with a respective spectral band. Each of at least three pixels in each of the spectral measurement lines is respectively associated with different respective pixel spectral bands. The different respective pixel spectral bands are non-identical to any one of the single spectral responses associated with each of the imaging spectral lines.

Combined spectral measurement and imaging sensor

A method identifies at least one malfunctioning nozzle in a digital printing press, the digital printing press including a plurality of nozzles. The method includes printing a design on a substrate, acquiring at least one image of the printed design and identifying at least one artifact in the acquired image. The method further includes identifying the malfunctioning nozzle and classifying the at least one malfunctioning nozzle according to the at least one of the acquired image of the printed design, at least a portion of a nozzle pattern and at least a portion of a uniformity pattern.

System and methods for detecting malfunctioning nozzles in a digital printing press

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Ramat Hasharon, Israel

Barry Ben Ezra