Patent classifications
G06V30/186
REPAIRING HOLES IN IMAGES
A method for image processing that includes: obtaining a mask of a connected component (CC) from an image; generating a stroke width transform (SWT) image based on the mask; calculating multiple stroke width parameters for the mask based on the SWT image; identifying a hole in the CC of the mask; calculating a stroke width estimate for the hole based on the stroke width values of pixels in the SWT image surrounding the hole; generating a comparison of the stroke width estimate for the hole with a limit based on the multiple stroke width parameters for the mask; and generating a revised mask by filling the hole in response to the comparison.
RECOGNITION AND INDICATION OF DISCRETE PATTERNS WITHIN A SCENE OR IMAGE
Selection of on optical pattern in a scene is identified by overlaying, on a display, an indicator of a detected optical pattern identifying a location of the optical pattern in one or more images, receiving a user input on the display at a position that does not overlap the location of the optical pattern, and presenting information related to the optical pattern, based on receiving the user input, even though the position of user input did not overlap the location of the optical pattern. The user input can be received at a detached selection indicator and/or using an adaptive input area.
RECOGNITION AND INDICATION OF DISCRETE PATTERNS WITHIN A SCENE OR IMAGE
Selection of on optical pattern in a scene is identified by overlaying, on a display, an indicator of a detected optical pattern identifying a location of the optical pattern in one or more images, receiving a user input on the display at a position that does not overlap the location of the optical pattern, and presenting information related to the optical pattern, based on receiving the user input, even though the position of user input did not overlap the location of the optical pattern. The user input can be received at a detached selection indicator and/or using an adaptive input area.
IMAGE ANALYSIS FOR MAPPING OBJECTS IN AN ARRANGEMENT
Image analysis is used to map objects in an arrangement. For example, images of a retail shelf are used to map items for sale on the retail shelf. A first vector can used to identify a relative position of a first item on a shelf to a shelving diagram, and a second vector can be used to identify a relative position of a second on the shelf to the shelving diagram, using locations of optical codes (e.g., barcodes). Absolution positions can be calculated. In some configurations, multiple images having different fields of view are matched to an overview image.
Image analysis for tracking, decoding, and positioning multiple optical patterns
Image analysis is used to track multiple optical patterns, such as barcodes. Many applications are becoming web-based. However, web-based applications can have less computational resources than a native application. For example, a native application can be used to track barcodes based on decoding barcodes from a plurality of images. However, decoding barcodes can be computationally intense and cause lag when moved to a web-based platform. To reduce computational resources used for decoding barcodes, barcodes are tracked in several frames and decoded only periodically for a web-based application used to decode barcodes. Positions of barcodes can be tracked relative to each other to form a digital shelf. The digital shelf can be used to visualize a state of a shelf.
Object pose neural network system
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium for predicting object pose. In one aspect, a method includes receiving an image of an object having one or more feature points; providing the image as an input to a neural network subsystem trained to receive images of objects and to generate an output including a heat map for each feature point; applying a differentiable transformation on each heat map to generate respective one or more feature coordinates for each feature point; providing the feature coordinates for each feature point as input to an object pose solver configured to compute a predicted object pose for the object, wherein the predicted object pose for the object specifies a position and an orientation of an object; and receiving, at the output of the object pose solver, a predicted object pose for the object in the image.
Recognition and selection of discrete patterns within a scene or image
A method of image analysis is provided for recognition of a pattern in an image. The method includes receiving a plurality of images acquired by a camera, where the plurality of images include a plurality of optical patterns in an arrangement. The method also includes matching the arrangement to a pattern template, wherein the pattern template is a predefined arrangement of optical patterns. The method also includes identifying an optical pattern of the plurality of optical patterns as a selected optical pattern based on a position of the selected optical pattern in the arrangement. The method also includes decoding the selected optical pattern to generate an object identifier and storing the object identifier in a memory device.
Document fraud detection
Systems and methods provide for a document fraud detection system for identifying fraudulent documents. The document fraud detection system can include up to three steps of fraud detection, where if the document fails any of the three steps, the document can be flagged for further review. In another embodiment, the document fraud detection system can score each of the three tests, where the scores represent the likelihood that the document is fraudulent. If the combined score satisfies a predetermined criterion, the document can be flagged as potentially fraudulent. The three tests can include analyzing a scanned image of the document and comparing to other similar documents to determine if there have been any alterations. The second test can compare indents to previous documents, and the third test can analyze chemical and biometric factors that may indicate whether the document has been altered.
Image analysis for mapping objects in an arrangement
Image analysis is used to map objects in an arrangement. For example, images of a retail shelf are used to map items for sale on the retail shelf A first vector can used to identify a relative position of a first item on a shelf to a shelving diagram, and a second vector can be used to identify a relative position of a second on the shelf to the shelving diagram, using locations of optical codes (e.g., barcodes). Absolute positions can be calculated. In some configurations, multiple images having different fields of view are matched to an overview image.
Image analysis for mapping objects in an arrangement
Image analysis is used to map objects in an arrangement. For example, images of a retail shelf are used to map items for sale on the retail shelf A first vector can used to identify a relative position of a first item on a shelf to a shelving diagram, and a second vector can be used to identify a relative position of a second on the shelf to the shelving diagram, using locations of optical codes (e.g., barcodes). Absolute positions can be calculated. In some configurations, multiple images having different fields of view are matched to an overview image.