Enhancement Method of Visual Aeronautical Chart for Small Target Elements
Augmented map is a new product of the combination of augmented reality and cartography.Due to the difficulty of tracking registration algorithm in recognizing small target features,most of the existing researches focus on the enhanced representation of global surface elements.In this paper,aiming at the recognition and enhance-ment design of small target point symbols,a visual aeronautical chart enhancement method based on YOLOv3 tar-get detection model is implemented,which mainly focuses on retrieval,reading and diversified symbol expression.The problem of symbol recognition of aeronautical elements is solved by using deep convolutional neural network.Three kinds of enhanced functions are designed based on the detection results.Experimental results show that this method can enhance the aeronautical elements in real time,and the detection model has good accuracy and recall rate,which can meet the small target enhancement requirements of visual aeronautical map elements.
万方数据
维普
