Acquiring a current image from an inputted video and a background model which comprises a background image and foreground/background classification information of visual elements; classifying the visual elements in the current image as foreground or background; determining similarity measures between the current image and groups in the background model, wherein visual elements in the current image are the visual elements in the current image which are classified as the foreground, wherein visual elements in the groups in the background model are the visual elements whose classification information is the foreground, and wherein the visual elements in the groups in the background model are the visual elements which neighbour to corresponding portions of the visual elements in the groups in the current image; and identifying whether the visual elements in the current image which are classified as the foreground are falsely classified or not according to the determined similarity measures.

Embodiments herein describe tracking the location and orientation of a target in a digital image. In an embodiment, this tracking can be used to control navigation for a vehicle. In an embodiment, a digital image can be captured by a visual sensor is received. A first array including a plurality of binary values related to the pixel velocity of a first plurality of pixels in the digital image as compared to corresponding pixels in a first one or more prior digital images can be generated. A second array including a plurality of values related to the standard deviation of pixel intensity of the first plurality of pixels in the digital image as compared to corresponding pixels in a second one or more prior digital images can be further generated. A plurality of thresholds relating to the values in the second array can be determined. A plurality of target pixels and a plurality of background pixels can be identified in the digital image, based on the first array, the second array, and the plurality of thresholds. A binary image related to the digital image, based on the identified plurality of target pixels and the identified plurality of background pixels, and identifying at least one of a location and an orientation of the target in the digital image based on the binary image, can be generated. In an embodiment, a command can be transmitted to a navigation system for a vehicle, to assist in navigating the vehicle toward the target, based on the identified at least one of a location and an orientation of the target.

A calibration method and a calibration device of a vehicle-mounted camera, a vehicle and a storage medium are provided. The calibration method includes: obtaining an original image including a plurality of first lane lines and captured by the vehicle-mounted camera; determining a region of interest (ROI) including the plurality of first lane lines in the original image; adjusting a pitch angle of the vehicle-mounted camera by detecting a plurality of second lane lines in a first inverse perspective mapping (IPM) image corresponding to the ROI, the second lane lines corresponding to the first lane lines; and adjusting a yaw angle of the vehicle-mounted camera by detecting an IPM binary image of a second IPM image corresponding to the ROI.

Among other things, the present disclosure relates to image searching. With a depth map, image pixels of an image having depth values intersecting a desired optical field can be identified. A territory can be set based on locations of the identified image pixels. Feature detection can be performed on the image within the set territory. The feature detection can be limited to the set territory.

A user device associated with a user may receive a document associated with the user. The user device may encrypt the received document. The user device may perform patch-based document segmentation on the received document to form a plurality of patches on the received document. The user device may extract text from each patch of the plurality of patches. The user device may analyze the extracted text from each patch to detect a field title and a field value. The user device may encrypt the extracted text and its associated field value for each patch of the plurality of patches. The user device may send the encrypted extracted text and its associated field value to the user device and instructions to display the extracted text and its associated field value on a user interface.

Disclosed herein is a method and device for identifying bold text in a digital document. The system receives image of digital document which comprises text. The system applies bounding box for each text in the image and scans predefined number of lines in each bounding box to identify width values of pixels. Thereafter, system identifies most occurring width value of pixels among the width values of pixels in each bounding box. The most occurring width value of pixels in each bounding box is identified as box width of corresponding bounding box. The system compares box width of each bounding box with threshold box width. If box width is greater than threshold box width, system identifies text of the bounding box whose box width exceeds threshold box width as bold text. The present disclosure efficiently identifies bold text in digital document based on width values of pixels with less computational power.

An apparatus may include an ultrasonic sensor system, a low-frequency vibration source and a control system. The ultrasonic sensor system may include an ultrasonic receiver and an ultrasonic transmitter configured for transmitting ultrasonic waves in a first frequency range (e.g., 1 MHz to 30 MHz). The low-frequency vibration source may be configured for generating low-frequency vibrations in a second frequency range (e.g., the range of 5 Hz to 2000 Hz). The control system may be configured for synchronizing the generation of the first low-frequency vibrations and the transmission of the first ultrasonic waves.

An image processing system adapted to binarize images is provided. The system includes a component detector configured to receive an image and detect a plurality of components in the image. The components are detected based on a content of the image. Further, the system includes a logical splitter configured to split the image into a plurality of windows based on the plurality of components. The plurality of windows is of varying window sizes. In addition, the system includes a threshold detector configured to determine a binarization threshold value for each window. The system also includes a binarization module configured to binarize a plurality of component images based on the corresponding binarization threshold values of the component. Furthermore, the system includes a logical integrator configured to generate a binarized image. The binarized image is a logically integrated image comprising the plurality of component images.

Techniques for binarization and extraction of information from image data are disclosed. The inventive concepts include independently binarizing portions of the image data on the basis of individual features, e.g. per connected component, and using multiple different binarization thresholds to obtain the best possible binarization result for each portion of the image data. Determining the quality of each binarization result may be based on attempted recognition and/or extraction of information therefrom. Independently binarized portions may be assembled into a contiguous result. In one embodiment, a method includes: identifying a region of interest within a digital image; generating a plurality of binarized images based on the region of interest using different binarization thresholds; subjecting the region of interest within a digital image to a plurality of thresholding and extraction iterations; and extracting data from some or all of the plurality of binarized images. Corresponding systems and computer program products are disclosed.

A device may receive digital content and may process the digital content, with at least one of an optimization-based poisoning model or a statistical-based poisoning model, to generate at least one of first poisoning data or second poisoning data, respectively. The device may generate new digital content based on the digital content and the at least one of the first poisoning data or the second poisoning data. The device may provide the new digital content to one or more devices to be accessed by at least one deepfake model used to create fake digital content and may perform one or more actions based on the new digital content.