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Night Vision Sensor

As the automotive night vision helps overcome visiual limitations under various environmental conditions(fog, rain, tec), it is being used as the device to ensure safer driving. Due to such features, automotive night vision is recognized as a mandatory sensor for upcoming "self driving age.

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Hanwha Systems' Night Vision Video Image

Thermal imaging camera installed with high resolution QuantumRed can complement automotive's ADAS(Advanced Driver Assistance System).
Costs were drastically cut down by introducting efficient processes and in-house production, which resolved the existing high cost issue.

Night Vision?

In order to fully implement self driving, it is mandatory to utilize sensors that can identify the driving conditions under whatever environmental conditions on a real time basis.
Radar is a sensor proven to be highly reliable regardless of external environmental conditions, but is not capable of providing object identifications or video images.
Also, while daytime camera can discern and identify small details of objects, its operation range is short and under poor visibility condition or during night time, its operations are limited.

With radar and daytime camera only, the two sensors being most widely used, it would be much difficult to overcome various conditions such as ① inclement weathers (rain, fog, etc.) ② nighttime ③ unexpected situations while driving, etc.

As Hanwha Systems' Night Vision is a passive type device that detects the heat generated by object itself by using far-infrared light sensor, it can detect, recognize and identify the objects regardless of external environmental conditions.

Advantages of
Night Vision

By using deep-learning technology, QuantumRed can make accurate pattern recognition of various objects such as vehicle, pedestrian, or animal, etc., and allow for more than 300m of detection/recognition distance before collision. This highly effective self driving sensor helps drivers to anticipate and avoid dangerous situations like collision while driving.

In addition, Night Vision was previously not so affordable due to its high cost structure. We will cut down the costs by introducing efficient processes as well as in-house production in order to expand its applications to self driving cars.