Scandit Ag

Oliver Akermann

Bernd Schoner

Christian Kündig

Luc Humair

Thibault Priquel

Moritz Zimmermann

Sebastien Roch

A method for decoding an optical pattern includes transmitting instructions for a first device to provide a link and an encryption key to a second device. The link includes a URL and a session ID that the first device has with a website. The method includes receiving a web request made by the second device using the URL. The method includes transmitting decoding software to the second device for decoding fields of a document based on image analysis of an image acquired by the second device. The method includes receiving decoded data from the second device. The method includes transmitting the decoded data to the website through a server in which the server uses only volatile memory to store the decoded data.

Secure ID scanning using image analysis

An identity document can be authenticated using format data of a barcode on the document, such as a barcode on a driver's license.

Local verification of an identity document based on optical pattern recognition

A camera on a robot is used to acquire images of a shelving unit. Locations of labels are detected and cropped from the images to form segments. The segments are analyzed to obtain scan descriptions, without decoding barcodes on the labels. The scan descriptions are compared to catalog descriptions to match scan descriptions to catalog descriptions. Products can then be mapped within an environment.

Building a catalog based on optical recognition of patterns in images

A camera is used to acquire images. Labels are detected in the images. The labels contain a barcode and product information. The product information is analyzed (e.g., by optical character recognition) to obtain a plurality of scan descriptions. Scan descriptions are matched with catalog descriptions to obtain stock keeping units (SKUs). The SKUs are mapped to locations within an environment based on position data of the camera at the time images are acquired.

Mapping items to locations within an environment based on optical recognition of patterns in images

An image is acquired by a camera. The image has a first set of characters and a second set of characters. The first set of characters are classified as an identifier. The second set of characters are classified as data associated with the identifier. The image is divided to create an image segment. The image segment includes the first set of characters and not the second set of characters. The first set of characters are decoded in the image segment to generate a first character string. The second set of characters are decoded to generate a second character string. The first character string is linked to the second character string based on classifying the first set of characters as the identifier and the second set of characters as the data associated with the identifier.

Classifying and segmenting characters within an image

An identity document can be authenticated using format data of a barcode on the document, such as a barcode on a driver's license. Scan data is obtained by decoding a plurality of barcodes. Format features of the plurality of barcodes are extracted. Scan data is classified into two or more clusters. Each cluster is characterized by a set of format features extracted from the scan data. A barcode on an ID to be verified is scanned. Format features from the barcode of the ID to be verified is compared to at least one of the two or more clusters to authenticate the ID.

Identity document verification based on barcode structure

Image analysis using visual geometry as an anchor for optical character recognition can be configured to receive an image acquired by a camera. The image is analyzed to detect a location within the image having a specified geometry. The specified geometry can be a predefined, visual geometry. The image is divided to create an image segment, where the image segment is based on the location of the specified geometry within the image. The image segment is analyzed to detect one or more characters within the image segment. The one or more characters in the image segment are decoded. A character string is generated based on decoding the one or more characters in the image segment.

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Zurich, Switzerland

Oliver Akermann