A workpiece image search apparatus includes: a workpiece image deformation unit that generates a third workpiece image by deforming a second workpiece image so that a difference in workpiece shape between a first workpiece image and the second workpiece image becomes smaller, wherein the first workpiece image is obtained by projecting a first workpiece shape of a first workpiece on a two-dimensional plane, and the second workpiece image is obtained by projecting a second workpiece shape of a second workpiece on a two-dimensional plane; and a similarity calculation unit that calculates a similarity between the first workpiece shape and the second workpiece shape by comparing the third workpiece image with the first workpiece image.

A method and device for testing product quality are disclosed. The method for testing product quality comprises: acquiring an image of a product to be tested; testing the image by using a pre-trained neural network model to obtain a testing result output by the neural network model; when the testing result indicates that the product to be tested is a defective product, performing a secondary judgment on the testing result according to position information of defective feature pixels in the image in the testing result, and determining whether the product to be tested is qualified according to a secondary judgment result. The method has high test accuracy, ensures the quality of product and facilitates reducing the labor cost of test.

A computer-implemented method for evaluating an image classifier, in which a classifier output of the image classifier is provided for the actuation of an at least semi-autonomous robot. The evaluation method includes: ascertaining a first dataset including image data and annotations being assigned to the image data, the annotations including information about the scene imaged in the respective image and/or about image regions to be classified and/or about movement information of the robot; ascertaining regions of the scenes that are reachable by the robot based on the annotations; ascertaining relevance values for image regions to be classified by the image classifier; classifying the image data of the first image dataset with the aid of the image classifier; evaluating the image classifier based on image regions correctly classified by the image classifier and incorrectly classified image regions, as well as the calculated relevance values of the corresponding image regions.

A computing system including a processing circuit in communication with a camera having a field of view. The processing circuit is configured to perform operations related to detecting, identifying, and retrieving objects disposed amongst a plurality of objects. The processing circuit may be configured to perform operations related to object recognition template generation, feature generation, hypothesis generation, hypothesis refinement, and hypothesis validation.

A vision inspection system includes a sorting platform having an upper surface supporting parts for inspection, wherein the parts are configured to be loaded onto the upper surface of the sorting platform in a random orientation. The vision inspection system includes an inspection station including an imaging device. The vision inspection system includes a vision inspection controller receiving images and processing the images based on an image analysis model to determine inspection results for each of the parts. The vision inspection controller has a shape recognition tool configured to recognize the parts in the field of view regardless of the orientation of the parts on the sorting platform. The vision inspection controller has an AI learning module operated to customize and configure the image analysis model based on the images received from the imaging device.

Methods for calibrating metrology apparatuses and determining a parameter of interest are disclosed. In one arrangement, training data is provided that comprises detected representations of scattered radiation detected by each of plural metrology apparatuses. An encoder encodes each detected representation to provide an encoded representation, and a decoder generates a synthetic detected representation from the respective encoded representation. A classifier estimates from which metrology apparatus originates each encoded representation or each synthetic detected representation. The training data is used to simultaneously perform, in an adversarial relationship relative to each other, a first machine learning process involving the encoder or decoder and a second machine learning process involving the classifier.

Methods of autonomous diagnostic verification and detection of defects in the optical components of a vision-based inspection system are provided. The method includes illuminating a light panel with a first light intensity pattern, capturing a first image of the first light intensity pattern with a sensor, illuminating the light panel with a second light intensity pattern different than the first light intensity pattern, capturing a second image of the second light intensity pattern with the sensor, comparing the first image and the second image to generate a comparison of images, and identifying defects in the light panel or the sensor based upon the comparison of images. Systems adapted to carry out the methods are provided as are other aspects.

The present invention provides a food and/or beverage item counting device to be provided in a food and/or beverage item provision system including a transport path that passes along a customer table to transport carriers each configured to allow a food and/or beverage item to be placed thereon, the food and/or beverage item counting device including: a first information acquiring unit disposed upstream of the table and configured to acquire information relating to each of the carriers on the transport path; a second information acquiring unit disposed downstream of the table and configured to acquire information relating to each of the carriers on the transport path; and a first calculating unit configured to calculate the number of the food and/or beverage items taken out from the transport path to the table, wherein each of the carriers is provided with identification information for identifying the carrier.

An aspect is to provide a scanning device, a system, and a method in which an available communication band is not used up even if a plurality of scanning devices are connected to one unit of dedicated hardware. According to one embodiment, a scanning device includes: a camera configured to pick up an image; a reduction unit configured to reduce a data volume of an image corresponding to a merchandise to be outputted to an image recognition device from the image picked up by the camera; and an output unit configured to output the image with the reduced data volume to the image recognition device.

There are included a probe that can be arranged in an imaging field of view, a horizontal drive section for causing the probe to contact a side surface of a workpiece on a stage, a display section for displaying a model image, a contact position designation section for receiving designation of contact target position information in the model image, a characteristic amount information setting section for setting characteristic amount information, a measurement setting information storage section for storing a plurality of pieces of contact target position information and the characteristic amount information, and a measurement control section for identifying a position and an attitude of the workpiece from a workpiece image by using the characteristic amount information, for identifying a plurality of contact target positions on the side surface of the workpiece where the probe should contact, based on the identified position and the identified attitude of the workpiece.