Abstract
The infrared target detection is a challenge task. In order to solve the lower signal-to-noise ratio, the lower resolution and the halo effect problems, we propose a novel detection approach based on fuzzy ART neural network. The fuzzy ART neural network is capable of rapid stable learning of recognition categories, and it can determine the total number of categories adaptively. At first, in the background modeling stage, the fuzzy ART neural networks were applied to classify the background and non-background categories, and the non-background categories were discarded so as to build the background model. Then the background model was combined with fuzzy ART neural networks to detect the targets. Experiments have been carried out and the results demonstrate that the proposed approach is robust to noise, and can eliminate the halo effectively. It can detect the targets effectively without much more post-process.
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