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Infrared Security Database

Welcome to the Infrared Security Database in the Infrared Open Source Database

Update date : 09/18/2021
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With the application and promotion of infrared imaging technology, more and more infrared technologies are used in intelligent security and transportation. In the security field, monitoring the surrounding environment using the infrared lens is an important means for 24-hour comprehensive monitoring. Due to characteristics of infrared images such as weak contrast and few details, they miss more information compared with common visible-light images. This increases the difficulties of detecting targets on infrared images. Currently, the key technical problem is to accurately detect and identify individuals and vehicles on infrared images. 


To deal with this problem, we have created a new infrared security people and vehicle identification database. Infrared imaging cameras are used to capture images on intersections in different periods, and a large set of infrared image data at the depression angle of monitoring equipment in real security scenarios are obtained for the database. The cameras are deployed 5 meters above the ground, and the angle is basically the same as the devices in real security scenarios. Infrared images in three different resolutions (384×288, 640×512, 704×576) are collected using different devices at different angles and heights. Then people, vehicles, and non-motor vehicles are marked in the images. This database will be primarily used for target detection and identification technology researches in the real-world infrared security field, promoting the infrared target identification technologies and thus pushing the infrared technology forward in the application and development in fields of various industries.

Our researches aim to establish an infrared target detection database in real security scenarios and verify the actual application effect of the infrared security algorithm in real scenarios. This database includes 2000 images containing pedestrians, vehicles, and non-motor vehicles in nine different scenarios, on intersections or roads in different periods. In the database, vehicle, person, and NonMotorVehicle are used as the tags for people, vehicles, and non-motor vehicles, respectively. Targets are marked in rectangular boxes. The position of rectangular boxes is marked in the form of [x1, y1, x2, y2] with the left corner of the image as the origin of coordinates [0,0]. For the upper-left corner, x1 indicates its abscissa, and y1 indicates its ordinate. For the lower-right corner, x2 indicates its abscissa, and y2 indicates its ordinate. All tag information is saved in XML files. 



Researchers in this research:

LIU Qing (

XU Zhaofei (

JIN Ronglu

WANG Shuigen (

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