An Automated Teller Machine (ATM) terminal receives a transaction request from a user. The ATM terminal triggers a camera to capture a first image of the authentication media item presented by the user, where the first image of the authentication media item is embedded with a first unique code. The ATM terminal compares the first image of the authentication media item with a second image of the authentication media item that is associated with the user, where the second image of the authentication media item is embedded with a second unique code for verifying the user. The ATM terminal determines whether the first unique code corresponds to the second unique code. The ATM terminal conducts the transaction request if it is determined that the first unique code corresponds to the second unique code.

A display body includes a base material having a first region, a second region, and a third region. In the display body, the first region is formed with a code or an image of identification information, and the second region is formed with a hidden code containing information obtained by encoding at least a part of the identification information. An encrypted ciphertext is recorded in the third region, and the ciphertext is generated from at least one of the code of the identification information and the hidden code.

A method for reading machine-readable labels on a plurality of sample receptacles held by a sample rack. The sample rack is moved between first and second positions within a housing and a label reader is activated at each of a plurality of predetermined position between the first and second positions to read the machine-readable label of each of the plurality of sample receptacles.

A bearing component is an annular member with a two-dimensional code which has a shape with a maximum circumferential dimension longer than a maximum radial dimension or a maximum axial dimension. An individual identification method for the bearing component includes the steps of imaging while rotating the bearing component, detecting a line pattern of the two-dimensional code from a captured image, recognizing the two-dimensional code based on an extension direction of the line pattern, extracting corresponding registration information by referring to a database based on information of the two-dimensional code, and identifying the bearing component according to the extracted registration information.

A system includes a plurality of masks and a scanner device. A pattern of a semiconductor device is defined by each of the plurality of masks in a photolithography process. A first mask of the plurality of masks includes a first identification code configured to distinguish the first mask from remaining masks of the plurality of masks. The scanner device is configured to read the first identification code to select the first mask from the plurality of mask, in order to form the pattern of the semiconductor device on a substrate according to the first mask.

The present disclosure relates generally to the processing of machine-readable visual encodings in view of contextual information. One embodiment of aspects of the present disclosure comprises obtaining image data descriptive of a scene that includes a machine-readable visual encoding; processing the image data with a first recognition system configured to recognize the machine-readable visual encoding; processing the image data with a second, different recognition system configured to recognize a surrounding portion of the scene that surrounds the machine-readable visual encoding; identifying a stored reference associated with the machine-readable visual encoding based at least in part on one or more first outputs generated by the first recognition system based on the image data and based at least in part on one or more second outputs generated by the second recognition system based on the image data; and performing one or more actions responsive to identification of the stored reference.

A sufficient decoding processing time for each image acquired by performing high-speed imaging is secured to obtain a stable reading result, thereby enabling immediate output of the obtained reading result. A processing unit has a first core and a plurality of second cores. The first core instructs the second cores, presumed to be capable of immediately executing the decoding process or executing the decoding process next to a decoding process being currently executed, to execute the decoding process. The second cores are configured to be capable of simultaneously executing the decoding process on read images instructed by the first core at different timings.

One variation of a method for maintaining perpetual inventory within a store includes: accessing a radar scan of an inventory structure within a store; accessing an optical image of the inventory structure; identifying a product type associated with the slot in a region of the optical image; retrieving a volumetric definition of the product type; locating a slot volume defining the slot in the radar scan; extracting a volumetric representation of a set of product units intersecting the slot volume in the radar scan; segmenting the volumetric representation by the volumetric definition to calculate a quantity of the set of product units occupying the slot; and updating a stock record of the store to reflect the quantity of the set of product units occupying the slot.

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.

The present invention relates to a system and method for optimizing the placement, size, scannability, and effectiveness of optical labels, such as 2D barcodes or machine-readable labels like QR codes, on a specified medium. The system comprises a set of servers configured to execute an artificial intelligence (AI) algorithm, a set of user devices, and a database. The AI algorithm analyzes uploaded images of intended mediums for optical label placement, determines optimal placement, size, and orientation of the optical labels, and calculates individual scores for visibility, scannability, and likelihood of being noticed by potential users for each suggestion, then combines these into an overall readability score. The invention offers a user-friendly, efficient, and objective approach to optimizing optical label placement that is particularly effective for addressing considerations for physical object mediums.