Abstract: A method and apparatus for determining an auto white balance (AWB) gain based on determined depth information. The method may include receiving an image captured by an image sensor, determining depth information associated with the captured image, assigning weights to a plurality of illuminants based on the determined depth information, determining an auto white balance gain based on the assigned weights and statistics of the captured image, and applying the auto white balance gain to the captured image.

Abstract: An apparatus includes an initializer configured to adjust one or more settings of a camera prior to initialization of the camera. The one or more settings are adjusted based on an indication of motion detected using at least one measurement performed by a sensor device. The apparatus further includes a processing device configured to execute a camera application to initialize the camera after adjustment of the one or more settings.

Abstract: Aspects of the present disclosure relate to systems and methods for calibrating a flash for image capture. An example method may include receiving, from a camera, a first image of a scene captured with a first flash light source emitting light with a first color temperature and with a second flash light source emitting light with a second color temperature different from the first color temperature. The first flash light source and the second flash light source may be derived based on a first flash calibration setting of a number of stored flash calibration settings. The example method may also include determining a difference between a desired color characteristic for the first flash calibration setting and a color characteristic of the first image. The example method may further include adjusting the first flash calibration setting based on the determined difference.

Abstract: Aspects of the present disclosure relate to systems and methods for calibrating a flash for image capture. An example method may include receiving, from a camera, a first image of a scene captured with a first flash light source emitting light with a first color temperature and with a second flash light source emitting light with a second color temperature different from the first color temperature. The first flash light source and the second flash light source may be derived based on a first flash calibration setting of a number of stored flash calibration settings. The example method may also include determining a difference between a desired color characteristic for the first flash calibration setting and a color characteristic of the first image. The example method may further include adjusting the first flash calibration setting based on the determined difference.

Abstract: An image capture device that includes an adjustment circuit configured to monitor image parameters, generate updated image settings for the image capture device in response to the monitored image parameters, and transmit the updated image settings to one or more processors. The updated image settings configure the one or more processors to determine whether to transition the image capture device from a dynamic scene mode to a static scene mode based on a first image parameter included in the monitored image parameters, wherein the first image parameter is different from a second image parameter used to determine to transition the image capture device from the static scene mode to the dynamic scene mode, and to suspend generation of all or less than all of the updated image settings in response to determining to transition the image capture device from the dynamic scene mode to the static scene mode.

Abstract: A method and apparatus for determining an auto white balance (AWB) gain based on determined depth information. The method may include receiving an image captured by an image sensor, determining depth information associated with the captured image, assigning weights to a plurality of illuminants based on the determined depth information, determining an auto white balance gain based on the assigned weights and statistics of the captured image, and applying the auto white balance gain to the captured image.

Abstract: An image capture device that includes an adjustment circuit configured to monitor image parameters, generate updated image settings for the image capture device in response to the monitored image parameters, and transmit the updated image settings to one or more processors. The updated image settings configure the one or more processors to determine whether to transition the image capture device from a dynamic scene mode to a static scene mode based on a first image parameter included in the monitored image parameters, wherein the first image parameter is different from a second image parameter used to determine to transition the image capture device from the static scene mode to the dynamic scene mode, and to suspend generation of all or less than all of the updated image settings in response to determining to transition the image capture device from the dynamic scene mode to the static scene mode.

Abstract: A method and device for aligning an image of a printed substrate using a mobile device. The method includes receiving, by an image capturing device, an image stream of a printed substrate; determining, by a processing device operably connected to the image capturing device, a location and a geometry of the printed substrate from the image stream; displaying, on a display operably connected to the processing device, the image stream; overlaying, by the processing device, at least a first visual marker onto the printed substrate as displayed in the image stream using the location and geometry; and instructing, by the processing device, a user of the mobile device to move the mobile device to align the mobile device and the printed substrate. The device includes the various hardware components configured to perform the method of aligning.

Abstract: This application relates to capturing an image of a target object using information from a time-of-flight sensor. In one aspect, a method may include a time-of-flight (TOF) system configured to emit light and sense a reflection of the emitted light and may determine a return energy based on the reflection of the emitted light. The method may measure a time between when the light is emitted and when the reflection is sensed and may determine a distance between the target object and the TOF system based on that time. The method may also identify a reflectance of the target object based on the return energy and may determine an exposure level based on a distance between the target object and a reflectance of the target object.

Abstract: An apparatus includes an initializer configured to adjust one or more settings of a camera prior to initialization of the camera. The one or more settings are adjusted based on an indication of motion detected using at least one measurement performed by a sensor device. The apparatus further includes a processing device configured to execute a camera application to initialize the camera after adjustment of the one or more settings.

Abstract: This application relates to capturing an image of a target object using information from a time-of-flight sensor. In one aspect, a method may include a time-of-flight (TOF) system configured to emit light and sense a reflection of the emitted light and may determine a return energy based on the reflection of the emitted light. The method may measure a time between when the light is emitted and when the reflection is sensed and may determine a distance between the target object and the TOF system based on that time. The method may also identify a reflectance of the target object based on the return energy and may determine an exposure level based on a distance between the target object and a reflectance of the target object.

Abstract: A method for determining parking availability includes receiving video data from a sequence of frames taken from an image capture device monitoring a parking area. The method includes detecting at least one object located in the parking area. The method includes determining boundaries of the parking area. The boundaries include at least an inner boundary relative to the image capture device and an outer boundary relative to the image capture device. The outer boundary is substantially parallel to the inner boundary. The method further includes computing a length of at least one of the object and a space between objects using an object pixel for each of the inner and outer boundaries. Using the computed length, The method includes determining a parking availability in the parking area. The method includes outputting a notice of the parking availability to a user.

Abstract: Certain aspects relate to systems and techniques for color temperature analysis and matching. For example, three or more camera flash LEDs of different output colors can be used to match any of a range of ambient color temperatures in a non-linear space on the black body curve. The scene color temperature can be analyzed in a preliminary image by determining actual sensor R/G and B/G ratios, enabling more accurate matching of foreground flash lighting to background lighting by the reference illuminant for subsequent white balance processing. The current provided to, and therefore brightness emitted from, each LED can be individually controlled based on the determined sensor response to provide a dynamic and adaptive mix of the output colors of the LEDs.

Abstract: Certain aspects relate to systems and techniques for color temperature analysis and matching. For example, three or more camera flash LEDs of different output colors can be used to match any of a range of ambient color temperatures in a non-linear space on the black body curve. The scene color temperature can be analyzed in a preliminary image by determining actual sensor R/G and B/G ratios, enabling more accurate matching of foreground flash lighting to background lighting by the reference illuminant for subsequent white balance processing. The current provided to, and therefore brightness emitted from, each LED can be individually controlled based on the determined sensor response to provide a dynamic and adaptive mix of the output colors of the LEDs.

Abstract: A system captures or otherwise receives a video and uses the video to create an electronic file corresponding to a multi-faceted printed artifact, such as a multi-page document. When the system receives the video, it selects a set of some or all of the video's image frames, determines a frame quality for each frame in the set, and identifies a subset of the frames such that the frame quality of each frame in the subset satisfies one or more image quality criteria. The subset will include at least one frame for each facet of the multi-faceted printed artifact, such as a page of the document. The processor then automatically combines the subset of frames into a single electronic file.

Abstract: Methods and systems for detecting an object borderline. A first image with respect to the object can be captured by an image-capturing unit without a flash light and borderlines of the object can be detected. If the detection is successful, the detected borderlines can be outputted. Otherwise, a second image with respect to the object can be captured by the image-capturing unit by applying a flash light and the borderlines can be detected in the image. A geometric transformation between the two images can then be estimated. Finally, the border lines in the first image can be determined by transforming the borderlines detected in the second image. Such an approach effectively detects the appliance borderlines and avoids artifacts caused by applying flash.

Abstract: A system and method of rendering in real time a virtual object onto a viewfinder display, the method comprising determining one or more scene properties of a scene on a viewfinder display of a device, receiving a virtual object for insertion into the scene, determining a location for placing the virtual object within the scene, determining a first appearance of the virtual object based on the one or more scene properties, and inserting the virtual object with the first appearance into the scene depicted on the viewfinder display of the device based on the location.

Abstract: A method of estimating one or more dimensions of a patch panel may include receiving an image of a patch panel that comprises a plurality of ports and one or more gaps, extracting, by a computing device, a region of interest from the received image, detecting, by the computing device, one or more line segments from the region of interest, determining whether one or more candidate ports can be identified based on at least a portion of the line segments, and in response to determining that one or more candidate ports can be identified, identifying one or more candidate ports, and determining, by the computing device, a gap length associated with the identified candidate ports.

Abstract: A method and device for receiving an image of a symbology captured by an imaging device, displaying an image of the symbology, displaying a boundary indicator around the symbology, adjusting the image size to correspond with the boundary indicator, decoding the symbology, and initiating an action by device.

Abstract: A method for processing an image of a patch panel includes: a) receiving an initial image; b) determining multiple ports of the patch panel are aligned in a desired orientation in the initial image; c) processing the initial image to identify edge lines perpendicular to the desired orientation; d) processing the edge lines to identify a port hypothesis that includes an estimated port gap between the multiple ports along the desired orientation and an estimated port size for the multiple ports along the desired orientation; e) processing the port hypothesis to determine an estimated port quantity for the multiple ports; and f) processing the port hypothesis to identify an estimation error between expected and detected edge line positions in relation to a reference axis perpendicular to the edge lines. An apparatus associated therewith includes an input/output and pre-processing modules and detection, hypothesis, estimating, and scoring processors.