Disclosed are an image sensing device and an operating method thereof, and the image sensing device may include: an image sensor including a plurality of pixels and suitable for generating an image based on incident light; and an image processor suitable for generating a high dynamic range (HDR) image based on the image and two or more pieces of tone mapping information, which are divided according to luminance.

The present specification discloses an apparatus and method for controlling the brightness of light to calculate more accurate figures as compared to when the level of a component in blood is measured through a change in color of a reaction reagent. A light control apparatus for a colorimetric method according to the present specification can control light to have a second brightness different from a first brightness while a camera captures an image of the reaction of a reagent and a sample. Thus, a wider range of measurement than conventional measurement ranges is possible.

In an information processing apparatus, a captured image acquiring section acquires data of an image captured of a reference object while part of incident light applied thereto is being blocked. An incident light information acquiring section acquires, according to a predetermined model equation, a brightness distribution of partial incident light in each of light-blocked states on the basis of the image of the reference object, and acquires a brightness distribution of overall incident light by calculating brightness distributions of partial incident light. A target information acquiring section acquires the shape and material of a target by using the brightness distribution of overall incident light.

An eyeball tracking method is provided. A left infrared light source and a right infrared light source are alternately turned on. A left tracking camera and a right tracking camera are controlled to correspondingly shoot the turned-on left infrared light source or the turned-on right infrared light source to form turned-on odd-frame tracking images and turned-on even-frame tracking images. Turned-off even-frame tracking images and turned-off odd-frame tracking images when the left infrared light source and the right infrared light source are alternately turned off in sequence are obtained according to the turned-on odd-frame tracking images and the turned-on even-frame tracking images. The turned-on odd-frame tracking images and the turned-off even-frame tracking images are combined to form a tracking image of one eye, and the turned-on even-frame tracking images and the turned-off odd-frame tracking images are combined to form a tracking image of the other eye.

An electronic device includes a display; a camera; a memory; and a processor operatively connected to the display, the camera, and the memory where the memory stores instructions which, when executed, enable the processor to determine a number of at least one source frame per unit second based on a specified maximum exposure time, receive light reflected from an external object by using the camera, for an exposure time determined according to a specified exposure value, generate source frames based on the received light, and generate a time-lapse image including at least one target frame indicating movement of the external object based on source frames, and the instructions cause the processor to generate the source frames at a speed different from a speed at which the time-lapse image including the at least one target frame is played.

An object detection device includes an irradiation unit, a light reception unit and a detection unit. The light reception unit is configured to receive reflected light of light radiated by the irradiation unit and environment light. The detection unit is configured to detect a predetermined object based on a point group that is information based on the reflected light and at least one image. The point group is a group of reflection points detected in the whole distance measurement area. The at least one image includes an environment light image that is an image based on the environment light, a distance image that is an image based on a distance to an object detected on a basis of the reflected light and/or a reflection intensity image that is an image based on reflection intensity of the reflected light.

Provided are a vision sensor, an image processing device including the vision sensor, and an operating method of the vision sensor. The vision sensor includes a plurality of pixels arranged in a matrix form, wherein each of the plurality of pixels includes: a sensing circuit configured to output an output voltage by sensing a change of light; a comparison circuit configured to output a comparison signal indicating whether an event has occurred by comparing the output voltage to an event threshold; and an event detection circuit configured to generate internal event signals by sampling the comparison signal at each of a plurality of sampling time points, and configured to output a valid event signal based on the internal event signals.

An image pickup apparatus, a control method thereof, and a storage medium, the image pickup apparatus being capable of shooting a plurality of still images under an appropriate exposure condition when the image pickup apparatus including a camera system performs alignment composition of the still images shot in a time continuous manner. An exposure time for each of the still images and a total number of the still images are set based on the focal length information, the optical image blur correction angle information, and the response characteristic information.

An apparatus includes a capturing unit configured to capture an image of an object, an exposure control unit configured to control an exposure condition including an exposure time or an analog gain for each of a plurality of pixels or pixel groups on a surface of the capturing unit, a determination unit configured to determine one or more evaluation areas including an achromatic color area from the captured image, a calculation unit configured to calculate a first evaluation value for each of the plurality of pixels or pixel groups in the evaluation area, and calculate a second evaluation value based on the first evaluation value weighted based on the exposure condition for each of the plurality of pixels or pixel groups, a correction unit configured to correct the image based on the second evaluation value.

A quantitative pulse count (event detection) algorithm with linearity to high count rates is accomplished by combining a high-speed, high frame rate camera with simple logic code run on a massively parallel processor such as a GPU or a FPGA. The parallel processor elements examine frames from the camera pixel by pixel to find and tag events or count pulses. The tagged events are combined to form a combined quantitative event image.