Disclosed, among other things, is a computer device and computer-implemented method of classifying cells within an image of a tissue sample comprising providing the image of the tissue sample as input; computing nuclear feature metrics from features of nuclei within the image; computing contextual information metrics based on nuclei of interest with the image; classifying the cells within the image using a combination of the nuclear feature metrics and contextual information metrics.

The present disclosure relates to a method for illustrating the ground underneath a vehicle using an around view monitoring system. The around view monitoring system comprises at least one camera, a processing unit and a display unit. The method comprises taking at least one image on the ground using at least one camera, tracking the position of the ground with respect to the vehicle and visualizing the ground as an under vehicle view and as a function of the vehicle speed, if the vehicle is moved over at least a portion of the ground. An around monitoring system is also provided.

Devices, systems, and methods enhance the inspection of internal areas and occupants of vehicles, and can employ one or more high-resolution cameras, one or more auxiliary illumination devices and a related computer system. According to various embodiments, an auxiliary illumination device can be synchronized to one or more cameras, and configured to supply auxiliary illumination to facilitate capture of accurate and usable images. Advanced image processing solutions assist with identifying individuals inside a vehicle, removing light glare and undesired reflections from a window surface, and capturing an image through a tinted window, among other things. Further, embodiments can compare a captured image to an authenticated image from a database, so as to confirm the identity of a vehicle occupant.

A display panel and a display device thereof are provided. The display panel comprises a display module comprising a first substrate and a first polarizer, wherein a light-exiting surface of the display module is arranged on an outer side of the first polarizer; a fingerprint recognition module disposed on an outer side of the first substrate and comprising a fingerprint recognition layer and a second polarizer disposed on an inner side of the fingerprint recognition layer; and a light source disposed on an inner side of the first polarizer. The fingerprint recognition layer recognizes fingerprint based on fingerprint signal light. The first polarizer is engaged with the second polarizer, such that the fingerprint signal light is transmitted through the first polarizer and the second polarizer without a light intensity loss, and the second polarizer reduces the light intensity of fingerprint noise light.

A cargo position tracking routine implemented in an electronic control unit of an automotive vehicle uses machine vision to monitor the position of cargo in a cargo area of an automotive vehicle and determine whether the cargo has shifted. Upon determining that the cargo has shifted, the cargo position tracking routine causes a driver of the vehicle to be alerted.

Imaging process initialization techniques are described. In an implementation, a color estimate is generated for a plurality of pixels within a region of an image. A plurality of pixels outside of the regions are first identified for each pixel of the plurality of pixels within the region. This may include identification of pixels disposed at opposing directions from the pixel being estimated. A color estimate is determined for each of the plurality of pixels based on the identified pixels. As part of this, a weighting may be employed, such as based on a respective distance of each of the pixels outside of the region to the pixel within the region, a distance along the opposing direction for corresponding pixels outside of the region (e.g., at horizontal or vertical directions), and so forth. The color estimate is then used to initialize an imaging process technique.

Systems, methods, and non-transitory computer-readable media can acquire an image that depicts at least one character. A set of pixels, within the image, through which the at least one character is depicted can be identified. At least one linear portion, within the image, can be identified based on the set of pixels. For each sub-portion within the at least one linear portion, a respective first confidence score representing a respective first likelihood that a respective sub-portion depicts the at least one character can be determined.

Methods and apparatus for using features of images representing content items to improve the presentation of the content items are disclosed. In one embodiment, a plurality of digital images are obtained, where each of the images represents a corresponding one of a plurality of content items. Image features of each of the digital images are determined. Additional features including at least one of user features pertaining to a user of a client device or contextual features pertaining to the client device are ascertained. At least a portion of the content items are provided via a network to the client device using features that include or are derived from both the image features of each of the plurality of digital images and the additional features.

A method for estimating the image depth map of a scene, includes the following steps: providing (E1) an image, the focus of which depends on the depth and wavelength of the considered object points of the scene, using a longitudinal chromatic optical system; determining (E2) a set of spectral images from the image provided by the longitudinal chromatic optical system; deconvoluting (E3) the spectral images to provide estimated spectral images with field depth extension; and analyzing (E4) a cost criterion depending on the estimated spectral images with field depth extension to provide an estimated depth map.

A system for capturing image data for gestures from a passenger or a driver in a vehicle with a dynamic illumination level comprises a low-lux sensor equipped to capture image data in an environment with an illumination level below an illumination threshold, a high-lux sensor equipped to capture image data in the environment with the illumination level above the illumination threshold, and an object recognition module for activating the sensors. The object recognition module determines the illumination level of the environment and activates the low-lux sensor if the illumination level is below the illumination threshold. If the illumination level is above the threshold, the object recognition module activates the high-lux sensor.