A mobile device configured to enable a user to maintain a facility includes: a display device; a network interface configured to communicate across a computer network with an external computer server to retrieve facility data; an antenna for interrogating an RFID tag; a reader configured to read a response signal generated by the RFID tag in response to the interrogating, process the response signal to extract tag information, determine whether the tag information includes information identifying one of a room within the facility or equipment within the facility; and a processor configured to determine whether the tag information includes a room identifier identifying a room within the facility or an equipment identifier identifying equipment within the facility based on the facility data, retrieve display data from the stored facility data based on the identified information, and present the display data on the display device.

In an image analyzing apparatus, identifying a barcode image includes: determining a bar candidate area representing a candidate for a bar having a first width in a target image, the bar candidate area containing a feature-matching area that matches a feature concerning two or more different widths of bars in a one-dimensional barcode; searching for first and second blank areas having lengths longer than or equal to a threshold value at first and second sides of the bar candidate area in a specific direction; when the first or second blank area is found, determining, as a first or second end position of the one-dimensional barcode, a boundary between the first or second blank area and a non-background area; and by using the first and second end positions, identifying an area containing the bar candidate area as the barcode image.

According to an embodiment, a moving image recognition apparatus includes a moving object detection unit, a data code reading unit, a label recognition unit, an association unit, and an output unit. The moving object detection unit detects moving objects from a moving image stored in a buffer unit and identifies each of the moving objects. The data code reading unit detects a data code from each frame of the moving image and decodes the detected data code. The label recognition unit detects and recognizes a label from each frame of the moving image. When the recognized label and the decoded data code exist on the same object, the association unit associates them. The output unit outputs together the decoding result of the data code and the recognition result of the label associated with the decoding result.

A facility for initiating a purchase is described. The facility receives a text sequence captured by a user from a rendered document using a handheld text capture device. The facility identifies in the received text sequence a reference to a distinguished product. In response to identifying the reference, the facility presents to the user an opportunity to place an order for the established product. If the user accepts the presented opportunity to order the distinct product, the facility orders the distinct product on behalf of the user.

In some arrangements, product packaging is digitally watermarked over most of its extent to facilitate high-throughput item identification at retail checkouts. Imagery captured by conventional or plenoptic cameras can be processed (e.g., by GPUs) to derive several different perspective-transformed views—further minimizing the need to manually reposition items for identification. Crinkles and other deformations in product packaging can be optically sensed, allowing such surfaces to be virtually flattened to aid identification. Piles of items can be 3D-modelled and virtually segmented into geometric primitives to aid identification, and to discover locations of obscured items. Other data (e.g., including data from sensors in aisles, shelves and carts, and gaze tracking for clues about visual saliency) can be used in assessing identification hypotheses about an item. Logos may be identified and used—or ignored—in product identification. A great variety of other features and arrangements are also detailed.

For scanning optical patterns, such as two-dimensional QR codes, with a mobile device at increased distances, a first image is acquired. A region of interest likely containing the optical pattern in the first image is identified. The mobile device then zooms in on the region of interest and a second image is acquired. The optical pattern is then decoded using the second image.

A method is provided. The method includes providing an authentication code onto a reference article associated with a person, determining a signature associated with the authentication code, imaging a candidate article to determine an image signature, and comparing the associated signature with the image signature to determine whether the candidate article is the reference article. A related system and imaging device are also provided.

The present disclosure provides a method for training a machine learning software component. In a computing system, a plurality of images and a plurality of location tuples are received. Each of the location tuples includes a subject identifier and a temporal identifier. For each of the location tuples, the subject identifier is associated with an image of the plurality of images using the temporal identifier to form a training data set. The machine learning software component is trained with the training data set.

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.

A mobile device includes a camera, a user interface system, and a processor communicatively coupled to the camera and the user interface system. The processor is typically configured for running a first application. The first application is typically configured for (i) accessing the camera, (ii) upon the initialization of the first application, initializing the camera, and (iii) maintaining the camera in an initialized state as long as the first application is running. The application may be further configured for focusing the camera and maintaining the camera in a focused state as long as the first application is running.