In order to further improve the accuracy and real-time performance of small infrared target detection

a new improved method is proposed. First

aiming at the characters of the infrared image

the improved Top-Hat filter is used to restrain background for the purpose of increasing the target detection probability. Second

the bound set is constructed to limit the gray level histogram to region of interest for reducing the interference of background and noise. Then target detection is achieved by image segmentation using improved OTSU algorithm. Furthermore

the fast recurring algorithm is applied to proposed algorithm for accelerating the running speed of the segmentation algorithm. Different types of infrared images are selected to compare the results of purposed algorithm and the other two algorithms in references. Experiment results show that proposed algorithm has better performance than the other two markedly. Object segmentation is more accurate and running speed is accelerated by more than 60%. Finally

the bound histogram can be constructed aiming at concrete problem

based on gained prior knowledge

so it has better generality.