The present disclosure relates to several types of finger vein sensor. In certain embodiments, the finger vein sensor includes: an image sensor, and an infrared light source. Image sensor captures infrared image of finger vein pattern of a finger of a target human. The image sensor faces down and is positioned at top of finger vein sensor. The infrared light source may include a predetermined number of infrared light-emitting diodes (LED), and they are arranged in one or more rows and one or more columns and positioned at bottom of finger vein sensor. The finger is positioned between infrared light source and image sensor. The infrared light from the infrared light source irradiates the finger vertically from the bottom to generate the infrared image of finger vein pattern of the finger on the image sensor, and the image sensor captures the infrared image of finger vein pattern of the finger.

Provided is an image processing device including an adjustment unit that adjusts any one of a background image which is a far-infrared image showing a background that does not include an object and a target image which is a far-infrared image showing the object, on the basis of a time change model of an observation pixel value, and an extraction unit that extracts a target region including the object in the target image on the basis of a result of comparison between the background image and the target image after the adjustment is performed.

A shutterless far-infrared (FIR) camera for advanced driver assistance systems, including at least one optical unit including at least one lens; an FIR sensor coupled to the optical unit and configured to capture FIR images; and an integrated circuit (IC) configured to process the captured FIR images to output an enhanced thermal video stream, wherein the IC further includes: a processing circuitry; and a memory containing instructions that, when executed by the processing circuitry, configure the processing circuitry to perform image corrections including at least a shutterless correction.

Provided is an imaging control device including: a processor; and a memory connected to or built in the processor. The processor acquires a first image by causing an image sensor of an imaging apparatus to image first light with a first sensitivity, and acquires a second image by causing the image sensor to image second light with a second sensitivity. The first sensitivity is a sensitivity for representing shape information of a subject with a first gradation in the first image. The second sensitivity is a sensitivity for representing temperature information of the subject with a second gradation in the second image.

Provided is an imaging control device including: a processor; and a memory connected to or built in the processor. The processor acquires a first image by causing an image sensor of an imaging apparatus to image first light with a first sensitivity, and acquires a second image by causing the image sensor to image second light with a second sensitivity. The first sensitivity is a sensitivity for representing shape information of a subject with a first gradation in the first image. The second sensitivity is a sensitivity for representing temperature information of the subject with a second gradation in the second image.

A multi-lane elevated body temperature preventative scanning solution using GigE vision and tracking. This multi-lane solution is used to scan and track movement of people through an elevated body temperature scanning solution. When a person enters the frame, their identity (ID) is tracked within the field of view of the thermal camera in a designated scanning area from there it is monitored through the entry and exit of a premise to acquire a preventative temperature screening. Multiple machine learning and tracking routines are used together in this innovative offering.

A multi-lane elevated body temperature preventative scanning solution using GigE vision and tracking. This multi-lane solution is used to scan and track movement of people through an elevated body temperature scanning solution. When a person enters the frame, their identity (ID) is tracked within the field of view of the thermal camera in a designated scanning area from there it is monitored through the entry and exit of a premise to acquire a preventative temperature screening. Multiple machine learning and tracking routines are used together in this innovative offering.

A wearable authentication system is provided. The wearable authentication system includes a head-mounted device and a ring device. The head-mounted device includes a first network module and a camera. The first network module sends an authentication request. The camera is configured to provide an image of a hand of a user. The ring device includes an inertial measurement unit, a second network module and a biometric sensor. The inertial measurement unit provides an inertial measurement value of the ring device. The second network module receives the authentication request. The biometric sensor gathers biometric information from the user based on the authentication request. The wearable authentication system tracks a position of the ring device based on at least one of the image and the inertial measurement value. The second network module sends authentication information based on the biometric information and the inertial measurement value to the first network module.

A wearable authentication system is provided. The wearable authentication system includes a head-mounted device and a ring device. The head-mounted device includes a first network module and a camera. The first network module sends an authentication request. The camera is configured to provide an image of a hand of a user. The ring device includes an inertial measurement unit, a second network module and a biometric sensor. The inertial measurement unit provides an inertial measurement value of the ring device. The second network module receives the authentication request. The biometric sensor gathers biometric information from the user based on the authentication request. The wearable authentication system tracks a position of the ring device based on at least one of the image and the inertial measurement value. The second network module sends authentication information based on the biometric information and the inertial measurement value to the first network module.

Embodiments of the present application provide an image fusion method and a bifocal camera. The method includes: acquiring a thermal image captured by the thermal imaging lens and a visible light image captured by the visible light lens; determining a first focal length when the thermal imaging lens captures the thermal image and a second focal length when the visible light lens captures the visible light image; determining a size calibration parameter and a position calibration parameter of the thermal image according to the first focal length and the second focal length; adjusting a size of the thermal image according to the size calibration parameter, and moving an adjusted thermal image to the visible light image according to the position calibration parameter for registration with the visible light image, to obtain to-be-fused images; and fusing the to-be-fused images to generate a bifocal fused image.