Warship detection in smoke screen interference background belongs to the field of object extraction from image with low contrast and low signal/noise ratio. Aimed at the specialty of the complex background, a novel algorithm of warship detection in smoke screen interference based on region of interest for CMAC-prediction is proposed in the article. The regions-of-interest (ROI) must be predicted in target tracking of IR image for increasing capture probability. CMAC estimator can effectually resolve conflict between operational counts and predicting precision. The local fractal dimension is used to differentiate the warship from the ROI. The experimental results show that CMAC can accurately estimate the ROI and a similar performance in a low-noise environment and superiority of the fractal operators in a high noise, the algorithms are effectively for smoke screen interference and are easy to be implemented by parallel processing hardware.
In this paper, a new algorithm for the detection of moving targets in smoke-screen image sequences is presented, which can combine three properties of pixel: grey, fractal dimensions and correlation between pixels by Rough Set. The first step is to locate and extract regions that may contain objects in an image by locally grey threshold technique. Secondly, the fractal dimensions of pixels are calculated, Smoke-Screen is done at different fractal dimensions. Finally, according to temporal and spatial correlations between different frames, the singular points can be filtered. The experimental results show that the algorithm can effectively increase detection probability and has robustness.
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