Datalogic IP Tech S.r.l.

Roberto Musiani

Maurizio De Girolami

Angelo Carraggi

Michele Benedetti

Francesco Deppieri

Alessandro Franchi

Enrico Campaioli

A retail store self-checkout area may include a scanner configured to enable a shopper to scan items being purchased. A bagging area may be positioned at the scanner. A top-down facing camera positioned and oriented to image a shopping cart or basket at the self-checkout area and to generate image signals of the shopping cart or basket. A projector may be configured to project dynamically alterable illumination signals onto a surface visible to the shopper when at the self-checkout area to provide visual guidance information to the shopper. The projector may be a smart projector, and may be configured to be a top-down facing projector to illuminate a floor at the self-checkout area. A system controller may be configured to drive the projector (e.g., smart projector) and to process images captured by camera to identify errors or fraudulent behavior during a self-checkout process.

Retail store self-checkout station and related methods for providing interactive virtual lane for smart self-checkouts

A system and method of detecting an image of a template object in a captured image may include comparing, by a processor, an image model of an imaged template object to multiple locations, rotations, and scales in the captured image. The image model may be defined by multiple model base point sets derived from contours of the imaged template object, where each model base point set inclusive of a plurality of model base points that are positioned at corresponding locations associated with distinctive features of the imaged template object. Each corresponding model base point of the model base point sets may (i) be associated with respective layers and (ii) have an associated gradient vector. A determination may be made as to whether and where the image of the object described by the image model is located in the captured image.

Imaging system and method using a multi-layer model approach to provide robust object detection

The disclosure relates to a data reading system and method for obtaining target data from an image. The data reading method includes obtaining an image containing the target data, and identifying a starting pixel coordinate on the image. The method further includes determining an initial local threshold value based on the selected starting pixel and analyzing the image to detect one or more high contrast boundaries or contours. After detecting the boundaries, the method includes analyzing the one or more boundaries to identify the target data in the image.

System and method for detecting optical codes with damaged or incomplete finder patterns

A method of acquiring images of an object arranged on a supporting surface includes providing at least one optical image acquisition apparatus of the object provided with an optical axis; in a work step of the optical apparatus an acquired image is processed to correct a possible perspective distortion of the image and at least one feature of the object is extracted from the processed image. The method further includes associating a known reference plane with the object and, in a configuration step of the optical apparatus preceding the work step, obtaining a corresponding inclination between the reference plane and the optical axis; processing the acquired image in fact comprises identifying a processing mode determined as a function of the corresponding inclination and applying this preset processing mode to correct the possible perspective distortion.

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Monte San Pietro, Italy

Roberto Musiani