Abstract: A virtual surface is used for a standby mode for a device scanning optical codes. A virtual surface is designating as a rendering target for a camera of a mobile device used to detect and decode optical codes. The camera is started, with the virtual surface designated as the rendering target for the camera. The camera is stopped, without terminating a program that uses the camera, wherein the camera is in a standby mode. The camera is restarted to render to the virtual surface, after stopping the camera. An optical code is detected in an image acquired by the camera, after restarting the camera from the standby mode.

Abstract: A camera is used to acquire images. Labels are detected in the images. The labels contain a barcode and product information. The product information is analyzed (e.g., by optical character recognition) to obtain a plurality of scan descriptions. Scan descriptions are matched with catalog descriptions to obtain stock keeping units (SKUs). The SKUs are mapped to locations within an environment based on position data of the camera at the time images are acquired.

Abstract: An angled optical pattern is decoded. To decode an optical pattern imaged at an angle, an area of interest of an image is received. A start line and an end line of the optical pattern are estimated. Corners of the optical pattern are localized. A homography is calculated based on the corners. And a scanline of the optical pattern is rectified based on the homography.

Abstract: 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.

Abstract: Visual odometry is used for tracking an optical pattern outside a preview area of a camera. The optical pattern is detected in a first image, while the camera is at a first position. A second image is acquired while the camera is at a second position. A transformation is calculated that relates the first position to the second position. A location of the optical pattern in relation to the second image is calculated based on the transformation. Calculation of the transformation can be simplified by assuming that the camera is moved in a plane parallel to a plane having multiple optical patterns.

Abstract: An image is acquired by a camera. The image has a first set of characters and a second set of characters. The first set of characters are classified as an identifier. The second set of characters are classified as data associated with the identifier. The image is divided to create an image segment. The image segment includes the first set of characters and not the second set of characters. The first set of characters are decoded in the image segment to generate a first character string. The second set of characters are decoded to generate a second character string. The first character string is linked to the second character string based on classifying the first set of characters as the identifier and the second set of characters as the data associated with the identifier.

Abstract: An optical pattern in a real scene is decoded after acquiring a video stream using a camera of a mobile device, wherein the video stream comprises preview images of the real scene and the optical pattern is in the real scene. A viewport for a screen of the mobile device is defined. The viewport is overlayed on an application window. The video stream is presented in the viewport, wherein at least a portion of the optical pattern is depicted in the viewport. The optical pattern is decoded in one or more images of the real scene acquired by the camera.

Abstract: Depth information from a depth sensor, such as a LiDAR system, is used to correct perspective distortion for decoding an optical pattern in a first image acquired by a camera. Image data from the first image is spatially correlated with the depth information. The depth information is used to identify a surface in the scene and to distort the first image to generate a second image, such that the surface in the second image is parallel to an image plane of the second image. The second image is then analyzed to decode an optical pattern on the surface identified in the scene.

Abstract: A digital camera in a mobile device, such as in a smart phone, can be used for super-fast scanning of optical codes.

Abstract: Incremental magnification is used to decode optical patterns, such a barcodes, in a scene. A first image of a scene is acquired using a first magnification of a camera, wherein the first image comprises a barcode. The barcode cannot be decoded. The magnification of the camera is increased by a predetermined magnification from the first magnification to a second magnification. A second image is acquired of the scene, including the barcode. The barcode is decoded after acquiring the second image.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: Described herein are embodiments of a mobile device case that allows a mobile device camera to view and/or capture images from multiple fields of view. The case may allow the mobile device camera to simultaneously capture image information from multiple different directions relative to the camera or mobile device. The fields of view may not be contiguous fields of view, such that there is a gap or other discontinuity between the fields of view. One field of view may be a field visible from or facing a surface of the mobile device on which the camera is disposed (e.g., the back of the mobile device) and another field of view may be one visible from or facing a different surface of the mobile device. Also described are embodiments of techniques for configuring a mobile device to capture and/or process images from multiple fields of view.

Abstract: An angled optical pattern is decoded. To decode an optical pattern imaged at an angle, an area of interest of an image is received. A start line and an end line of the optical pattern are estimated. Corners of the optical pattern are localized. A homography is calculated based on the corners. And a scanline of the optical pattern is rectified based on the homography.

Abstract: An identity document can be authenticated using format data of a barcode on the document, such as a barcode on a driver's license. Scan data is obtained by decoding a plurality of barcodes. Format features of the plurality of barcodes are extracted. Scan data is classified into two or more clusters. Each cluster is characterized by a set of format features extracted from the scan data. A barcode on an ID to be verified is scanned. Format features from the barcode of the ID to be verified is compared to at least one of the two or more clusters to authenticate the ID.

Abstract: A memory device is provided including instructions that, when executed, cause one or more processors to perform the steps including receiving a plurality of images acquired by a camera, the plurality of images including a plurality of optical patterns, wherein an optical pattern of the plurality of optical patterns encodes an object identifier. The steps include presenting the plurality of images comprising the plurality of optical patterns on a display, and presenting a plurality of visual indications overlying the plurality of optical patterns in the plurality of images. The steps also include identifying a selected optical pattern of the plurality of optical patterns based on a user action and a position of the selected optical pattern in one or more of the plurality of images. The steps also include decoding the selected optical pattern to generate the object identifier and storing the object identifier in a second memory device.

Abstract: Images of optical codes are mapped to an overview image to localize optical codes within a space. By localizing optical codes, information about locations of various products can be ascertained. One or more techniques can be used to map the images of optical codes to the overview image. The overview image can be a composite image formed by stitching together several images.

Abstract: Image analysis using visual geometry as an anchor for optical character recognition can be configured to receive an image acquired by a camera. The image is analyzed to detect a location within the image having a specified geometry. The specified geometry can be a predefined, visual geometry. The image is divided to create an image segment, where the image segment is based on the location of the specified geometry within the image. The image segment is analyzed to detect one or more characters within the image segment. The one or more characters in the image segment are decoded. A character string is generated based on decoding the one or more characters in the image segment.

Abstract: Image data from a camera and depth information from a depth sensor, such as a LiDAR system, are used to segment an image for decoding an optical pattern. The image data is spatially correlated with the depth information. The depth information is used to partition the image into one or more foreground segments and one or more background segments. Scanning for the optical pattern is performed on the one or more foreground segments.