Research on infrared ship detection method in sea-sky background

An approach to infrared ship detection based on sea-sky-line(SSL) detection, ROI extraction and feature recognition is proposed in this paper. Firstly, considering that far ships are expected to be adjacent to the SSL, SSL is detected to find potential target areas. Radon transform is performed on gradient image to choose candidate SSLs, and detection result is given by fuzzy synthetic evaluation values. Secondly, in view of recognizable condition that there should be enough differences between target and background in infrared image, two gradient masks have been created and improved as practical guidelines in eliminating false alarm. Thirdly, extract ROI near the SSL by using multi-grade segmentation and fusion method after image sharpening, and unsuitable candidates are screened out according to the gradient masks and ROI shape. Finally, we segment the rest of ROIs by two-stage modified OTSU, and calculate target confidence as a standard measuring the facticity of target. Compared with other ship detection methods, proposed method is suitable for bipolar targets, which offers a good practicability and accuracy, and achieves a satisfying detection speed. Detection experiments with 200 thousand frames show that the proposed method is widely applicable, powerful in resistance to interferences and noises with a detection rate of above 95%, which satisfies the engineering needs commendably.