Systems and methods are disclosed for locating a retroreflective object in a digital image and/or identifying a feature of the retroreflective object in the digital image. In certain environmental conditions, e.g. on a sunny day, or when the retroreflective material is damaged or soiled, it may be more challenging to locate the retroreflective object in the digital image and/or to identify a feature of the object in the digital image. The systems and methods disclosed herein may be particularly suited for object location and/or feature identification in situations in which there is a strong source of ambient light (e.g. on a sunny day) and/or when the retroreflective material on the object is damaged or soiled.

Systems and methods for ossification center detection (OCD) and bone age assessment (BAA) may be provided. The method may include obtaining a bone age image of a subject. The method may include generating a normalized bone age image by preprocessing the bone age image. The method may include determining, based on the normalized bone age image, positions of a plurality of ossification centers using an ossification center localization (OCL) model. The method may include estimating, based on the normalized bone age image and information related to the positions of the plurality of ossification centers, a bone age of the subject using a bone age assessment (BAA) model.

A method of obtaining a quantum efficiency distribution in a predetermined sample surface, including: irradiating a reference material with excitation light belonging to a first wavelength range; obtaining the reference material's image, which includes a first channel for the first wavelength range and a second channel for a second wavelength range, the first and the second channel's irradiation luminance value in each pixel; irradiating the predetermined sample surface with the excitation light; obtaining the first and the second channel's measurement luminance value in each pixel of the image of the predetermined surface; calculating an absorption luminance value from a difference between the first channel's irradiation luminance value and measurement luminance value; calculating a fluorescence luminance value from difference between the second channel's irradiation luminance value and measurement luminance value; calculating quantum efficiency of each pixel based on the values; and obtaining quantum efficiency distribution.

A multi-sensor spatial data auto-synchronization system and method is provided. The method may include collecting laser point cloud data through a laser radar and pre-processing the laser point cloud data; collecting image point cloud data through a monocular camera and collecting intrinsic parameters of the camera by using a calibration board; performing plane fitting on the pre-processed laser point cloud data to determine coordinates of fitted laser point cloud data; performing image feature extraction on the image point cloud data; calculating pose transformation matrices for the laser point cloud data coordinates and an image feature data result by using a PNP algorithm; and optimizing a rotation vector and a translation vector in the pose transformation matrix. The present invention achieves automatic calculation of a spatial synchronization relationship between two sensors, and greatly improves the data synchronization precision of the laser radar and the monocular camera.

This document describes techniques and systems that enable automatic exposure and gain control for face authentication. The techniques and systems include a user device initializing a gain for a near-infrared camera system using a default gain. The user device ascertains patch-mean statistics of one or more regions-of-interest of a most-recently captured image that was captured by the near-infrared camera system. The user device computes an update in the initialized gain to provide an updated gain that is usable to scale the one or more regions-of-interest toward a target mean-luminance value. The user device dampens the updated gain by using hysteresis. Then, the user device sets the initialized gain for the near-infrared camera system to the dampened updated gain.

According to an aspect of the present disclosure, a detection device includes: a substrate; a plurality of first optical sensors provided in a detection area of the substrate and comprising an organic material layer having a photovoltaic effect; and at least one or more second optical sensors provided on the substrate and comprising an inorganic material layer having a photovoltaic effect.

A method for image colorization includes receiving, from a camera, an input image including a plurality of input image pixels. One or more input interest pixels of the plurality of input image pixels are classified as corresponding to an object of interest. A display image is generated having a plurality of display image pixels each having pixel values based on relative temperature values of objects in a real-world environment, the display image pixels including display interest pixels corresponding to the input interest pixels. The display interest pixels are colorized with a color selected based on a recognized class of the object of interest to give a colorized display image, the selected color being independent of the relative temperature values of the object of interest. The colorized display image is displayed with the display interest pixels colorized with the selected color.

An image processing method includes receiving an input image and a guide image corresponding to the input image, extracting informative features from the input image and the guide image to enhance the input image, selectively obtaining a first feature for the input image from among the informative features, and processing the input image based on the first feature.

A computer vision method and computer vision system can be used to process a time-based series of images. For a subject image of the time-based series, a light intensity value is identified for each pixel of a set of pixels of the subject image. A light intensity threshold is defined for the subject image based on a size of a bounding region for an object detected within a previous image of the time-based series captured before the subject image. A modified image is generated for the subject image by one or both of: reducing the light intensity value of each pixel of a lower intensity subset of pixels of the subject image that is less than the light intensity threshold, and increasing the light intensity value of each pixel of a higher intensity subset of pixels of the subject image that is greater than the light intensity threshold.

A facial recognition process operating on a device may include one or more processes that determine if a camera and/or components associated with the camera are obstructed by an object (e.g., a user's hand or fingers). Obstruction of the device may be assessed using flood infrared illumination images when a user's face is not able to be detected by a face detection process operating on the device. Obstruction of the device may also be assessed using a pattern detection process that operates after the user's face is detected by the face detection process. When obstruction of the device is detected, the device may provide a notification to the user that the device (e.g., the camera and/or an illuminator) is obstructed and that the obstruction should be removed for the facial recognition process to operate correctly.