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.

Systems and methods for performing OCR of an image depicting text symbols and imaging a document having a plurality of planar regions are disclosed. An example method comprises: receiving a first image of a document having a plurality of planar regions and one or more second images of the document; identifying a plurality of coordinate transformations corresponding to each of the planar regions of the first image of the document; identifying, using the plurality of coordinate transformations, a cluster of symbol sequences of the text in the first image and in the one or more second images; and producing a resulting OCR text comprising a median symbol sequence for the cluster of symbol sequences.

Systems and methods for performing OCR of an image depicting text symbols and imaging a document having a plurality of planar regions are disclosed. An example method comprises: receiving a first image of a document having a plurality of planar regions and one or more second images of the document; identifying a plurality of coordinate transformations corresponding to each of the planar regions of the first image of the document; identifying, using the plurality of coordinate transformations, a cluster of symbol sequences of the text in the first image and in the one or more second images; and producing a resulting OCR text comprising a median symbol sequence for the cluster of symbol sequences.

An apparatus for raising livestock includes one or more confinement pens together with alleyways for transfer of the animals from one location to another. The apparatus includes one or more cameras for obtaining images of all animals in the containment area. A processor is provided for analyzing the images, the processor being arranged to allocate an arbitrary identification to each animal and to track all animals continually to maintain the allocation. From this tracking various data related to individual animals or the animals as a group can be obtained to assess their characteristics and to provide an indication to the worker of the animal to be extracted. The processor can be arranged to detect by image analysis of the image a quantity of feed and/or water in a feeder and to obtain images of the farrowing pen including the sow confinement area and at least one piglet confinement area.

An environment association system (“EAS”) comprising: a processor and a memory; an object recognition process configured to identify objects within images, the objects including one or more of a vehicle, a vehicle lift, a vehicle repair tool, and an alignment fixture; and an EAS interface configured to communicate with a user device, the user device comprising a camera and a display; wherein the processor is configured to: determine, for at least one object in the set of objects, create a virtual overlay for the image based on the position of the at least one object within the image and a virtual marking associated with the at least one object; and provide the virtual overlay to the user device, wherein the virtual overlay is configured to cause the user device to simultaneously display the image and the virtual overlay via the display. The system provides information about the alignment of lifting points of the object with lifting members.

An image processing system or electronic device may implement processing circuitry. The processing circuitry may receive an image, such as financial document image. The processing circuitry may determine a character count for the financial document image or particular portions of the financial document image without recognizing any particular character in the financial document image. In that regard, the processing circuitry may determine a top left score for pixels in the financial document, the top left score indicating or representing a likelihood that a particular pixel corresponds to a top left corner of a text character. The processing circuitry may also determine top right score for image pixels. Then, the processing circuitry may identify one or more text chunks using the top left and top rights scores for pixels in the financial document image. The processing circuitry may determine a character count for the identified text chunks.

An image processing system or electronic device may implement processing circuitry. The processing circuitry may receive an image, such as financial document image. The processing circuitry may determine a character count for the financial document image or particular portions of the financial document image without recognizing any particular character in the financial document image. In that regard, the processing circuitry may determine a top left score for pixels in the financial document, the top left score indicating or representing a likelihood that a particular pixel corresponds to a top left corner of a text character. The processing circuitry may also determine top right score for image pixels. Then, the processing circuitry may identify one or more text chunks using the top left and top rights scores for pixels in the financial document image. The processing circuitry may determine a character count for the identified text chunks.

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.).

Systems, methods and media are disclosed for identifying the crossing of a virtual barrier. A person in a 3D image of a room may be circumscribed by a bounding box. The position of the bounding box may be monitored over time, relative to the virtual barrier. If the bounding box touches or crosses the virtual barrier, an alert may be sent to the person being monitored, a caregiver or a clinician. Bounding box tracking may be used in addition to or instead of an initial tracking process, such as skeletal tracking.

A center-alignment apparatus for use in an ATM has a transport mechanism to transport a document into the ATM. One or more plates operable in tandem to move the document toward a centerline of a path the document is to travel. Edge-detection sensor(s) on the plate sense an edge of the document when the plate(s) is moved toward the centerline. A translate/rotate mechanism translates and rotates the document while the translate/rotate mechanism transversely moves the document toward the center until another edge-detection sensor detects an edge of the document to create a parallel-aligned document. The control logic controls the plate(s) to centers the parallel-aligned document about the centerline to create a centered document.