Detection of Weak Small Image Target Based on Brain-Computer Interface

The paper proposes an innovative frame for enhanced detection of targets in images based on EEG. In this study, we have achieved the process of long-term EEG signal in single trial. We have designed the experimental paradigms and performed the experiment on 12 subjects. We analyzed the EEG signals by extracting dynamic features. We determined the target detection according to single-trial EEG, simultaneously the target position by eye movement signals. The results proved that the method we adopted is significantly useful and reached satisfactory accuracy. Furthermore, the research can be used as a supplementary means for target detection of machine learning. By the fusion of human experience and intelligence, this work breaks through some bottlenecks of traditional target detection, such as the detection of uncertain targets, small targets, severely distorted targets and incomplete targets. It can significantly improve the detection rate of image information and compatible migration capability.