Infrared images have advantages such as strong anti-interference ability and working day and night, and have been widely used in important places monitoring, traffic management, and other fields. However, infrared images also have problems such as poor contrast and low signal-to-noise ratio, which result in the feature extraction of targets in infrared images not being visible and bright and cannot meet the needs of target recognition in complex backgrounds. Based on this, a fusion method combining interactive strokes-based Otsu method with morphological operations is proposed. This method is based on the principle of maximum inter class variance, maximum flow/minimum cut, and digital morphology to establish an image object extraction model, which takes into account the accuracy and noise resistance of image extraction.
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