A system performs a method for processing an image of a machine-readable code. The method includes receiving an image of a machine-readable code comprising coded information, where the machine-readable code is at least partially obscured by a substance that has a predominant color; generating an adjusted image by adjusting a color space of the image based on the predominant color; binarizing at least a machine-readable code region of the image, wherein the machine-readable code region of the image depicts the machine-readable code; and decoding the binarized machine-readable code region to determine the coded information. Other apparatus and methods are also described.

A camera-based barcode reader captures an image, determines a region of interest of a barcode within the image, and generates a barcode image from the region of interest. The camera-based barcode reader aligns each of multiple horizontal regions within the barcode image to a reference horizontal region within the barcode image. The alignment of a horizontal region includes (i) determining a set of alignment parameters to apply to the horizontal region based on a comparison of the reference horizontal region to the horizontal region when adjusted to different combinations of alignment parameters and (ii) adjusting the horizontal region according to the set of alignment parameters for that horizontal region. After aligning the barcode image, the camera-based barcode reader decodes the barcode from the barcode image.

A system, method, and computer-readable medium for accessing information associated with items within a multi-dimensional space, comprising: scanning a plurality of multi-dimensional symbols, each of the plurality of multi-dimensional symbols being scanned from a plurality of angles; identifying each of the plurality of multi-dimensional symbols for each angle; and storing information identifying each of the plurality of multi-dimensional symbols for each angle in an encoded geometry repository.

The present disclosure relates to a system and a method for extracting a computer readable code from a captured image of a mailpiece or parcel using downsampling and edge detection. The system can include a reader configured to capture an image of an item having a computer readable code positioned thereon and a processor in data communication with the reader. The processor can generate captured image data of the item including the computer readable code, downconvert the captured image data to generate a downconverted image data and detect an edge of the computer readable code. The processor can also identify a position of the computer readable code in the downconverted image data and store or process only the identified computer readable code.

The present disclosure relates to a system and a method for extracting a computer readable code from a captured image of a mailpiece or parcel using downsampling and edge detection. The system can include a reader configured to capture an image of an item having a computer readable code positioned thereon and a processor in data communication with the reader. The processor can generate captured image data of the item including the computer readable code, downconvert the captured image data to generate a downconverted image data and detect an edge of the computer readable code. The processor can also identify a position of the computer readable code in the downconverted image data and store or process only the identified computer readable code.

Aspects and implementations provide for mechanisms of detection and decoding of barcodes in images. The disclosed techniques include estimating dimensions of a module of a barcode based on geometric characteristics of a barcode image, forming hypotheses that group modules into barcode symbols, and assessing viability of formed hypotheses. Various operations of the techniques may involve the use of neural networks, including estimation of module dimensions and assessment of groupings of modules into lines and lines into barcode symbols. The techniques may be used for decoding of barcodes captured in images of unfavorable conditions, including blur, perspective, sub-optimal lighting, barcode deformation, and the like. The techniques may be applied to decoding linear one-dimensional barcodes, two-dimensional barcodes, and stacked linear barcodes.

Methods and apparatus to determine barcode decoding parameters for a plurality of barcodes in an image are disclosed. An example method includes: obtaining image data representing an image including a plurality of barcodes; decoding a first barcode of the plurality of barcodes from the image data; determining a set of barcode decoding parameters used to successfully decode the first barcode; determining whether the plurality of barcodes encoded using at least one of a same barcode size, a same module size, or a same barcode format; and when the plurality of barcodes are encoded using at least one of the same barcode size, the same module size, or the same barcode format, attempting to decode all remaining barcodes of the plurality of barcodes from the image data using first the set of barcode decoding parameters.

In some implementations, a device may receive, from a camera of a source device, video data depicting a physical environment. The device may detect a target indicator associated with a target zone of the physical environment. The device may determine, based on the target indicator, a zone configuration of the target zone relative to the target indicator. The device may generate, based on a position of the source device, an initial masking content that is associated with a boundary of the target zone that is defined by the zone configuration using a spatial mapping model based on the video data and the target indicator. The device may generate a final masking content using chroma keying based on the initial masking content. The device may generate display data associated with the final masking content and the video data. The device may provide the display data to a destination device.

A user instrument for engaging in a transaction includes a graphically encoded icon having a static portion, and an intrinsic portion comprising an area of stimuli-responsive material defining a first machine-readable indicia. At least a portion of the stimuli-responsive material transforms from a first state to a second state in response to a trigger. The transformation from the first state to the second state of the portion of the stimuli-response material results in a second machine-readable indicia. The transformation of the stimuli-responsive material from the first state to the second state is semi-irreversible. The second machine-readable indicia comprises information to permit or deny the user to engage in a second transaction via the user instrument.

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.