Abstract
Accurate and fast detection of infrared (IR) dim target has very important meaning for infrared precise guidance, early
warning, video surveillance, etc. In this paper, some basic principles and the implementing flow charts of a series of
algorithms for target detection are described. These algorithms are traditional two-frame difference method, improved
three-frame difference method, background estimate and frame difference fusion method, and building background with
neighborhood mean method. On the foundation of above works, an infrared target detection software platform which is
developed by OpenCV and MFC is introduced. Three kinds of tracking algorithms are integrated in this software. In
order to explain the software clearly, the framework and the function are described in this paper. At last, the experiments
are performed for some real-life IR images. The whole algorithm implementing processes and results are analyzed, and
those algorithms for detection targets are evaluated from the two aspects of subjective and objective. The results prove
that the proposed method has satisfying detection effectiveness and robustness. Meanwhile, it has high detection
efficiency and can be used for real-time detection.
