The present disclosure is related to an optical encoder which is configured to provide precise coding reference data by feature recognition technology. To apply the present disclosure, it is not necessary to provide particular dense patterns on a working surface. The precise coding reference data can be generated by detecting surface features of the working surface.

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.

Printing a code on a flexible medical solution container includes providing a flexible medical solution container which is at least partially light transmissive, storing in a memory circuit a code comprising numbers and translating the code comprising numbers using a bar code symbology, the bar code symbology defining dark areas and light areas. The method includes applying a light-reflective ink to the container based on the bar code symbology, wherein the light-reflective ink is applied in areas defined by the dark areas, and applying a light-absorbing ink to the container based on the bar code symbology, wherein the light-absorbing ink is applied in areas defined by the light areas. The applied light-reflective Ink and light-absorbing ink results in a code which represents a reversal of the dark and light areas defined in the bar code symbology.

A system includes one or more memory devices storing instructions, and one or more processors configured to execute the instructions to perform steps of a method. The system may provide an augmented environment that facilitates a transaction. The system may store profile data including user payment or user profile information. The system may then receive environmental data, and identify one or more action items in the environmental data. In response to this identification, the system may augment the environmental data by adding virtual environmental data, and then provide this virtual environmental data to a device to create an augmented environment. The system can then receive user input data, and provide purchase request data to a merchant terminal in response to those inputs.

An angled optical pattern is decoded. To decode an optical pattern imaged at an angle, an area of interest of an image is received. A start line and an end line of the optical pattern are estimated. Corners of the optical pattern are localized. A homography is calculated based on the corners. And a scanline of the optical pattern is rectified based on the homography.

Systems and methods for automatic identification and presentation of edges, shapes and unique objects in an image used for machine vision job setup are disclosed herein. An example method includes receiving, by one or more processors, an image file. The method further includes automatically determining, by the one or more processors, an item of interest within the image file. The method further includes analyzing, by the one or more processors, the item of interest to determine an appropriate tool for processing the item of interest. The method further includes displaying, by the one or more processors, on a display screen: (i) an image corresponding to the image file, (ii) an indication of the item of interest, and (iii) an indication of the appropriate tool.

Disclosed are a system and method to verify and authenticate an item. The system includes a memory and a processor. The processor includes a reader module, an optical character recognition (OCR) module, an image recognition module, a camera module, and an item digital passport (IDP) module. The reader module scans and processes a matrix barcode and other barcodes. The optical character recognition (OCR) module scans one or more of a micro size alphanumeric code, a nano size alphanumeric code, and a visible alphanumeric code present on a hologram that is embossed, printed, or lasered on the item and verifies the item by comparing the scanned data with the data corresponding to the item stored in the memory. The optical character recognition module authenticates the item if the scanned data matches with the data corresponding to the item stored in the memory. The optical character recognition module facilitates a user interface to display the comparison data and the authentication data. The image recognition module verifies and authenticates one or more of a micro size image, a nano size image, and a visible holographic image present on the hologram. The camera module analyzes the intricate details of one or more of the hologram features and elements, and a security print design features and elements captured by a camera lens. The camera module measures individual features and elements present in the hologram, and the security print design features and elements with an embedded ruler. The item digital passport (IDP) module captures data pertaining to the movement of the items from a source point to a destination point.

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.

An inspection method is provided for checking the integrity of a combination of a security marking and an identification label, the security marking including at least one contrast field having a comparatively high reflectivity in a first and a second wavelength range, and a security field, having different reflection properties in the first wavelength range compared to the second wavelength range, and the identification label having at least one light background around mark components printed with dark color. The inspection method may include capturing possibly averaged gray values of the contrast field and the identification label background, comparing the gray values, and determining whether the gray value of the contrast field of the security marking deviates from the gray value of the background of the identification label by less than a predefined maximum amount.

Disclosed is an approach of on-device partial recognition that includes performing partial recognition on an image of a document captured by a mobile device to detect and/or recognize a specific area (e.g., barcodes, non-relevant text, etc.) and filling the recognized area with a solid color. Because the solid color area has a maximum compression ratio, this approach can lead to image size reduction and increased network throughput for client-server based data recognition where further processing such as advanced data extraction is performed at the server side. The approach can be enforced with neural network algorithms to exclude non-relevant information (e.g., logos, phrases, words, etc.).