Automated Extraction Information System from HUDs Images Using ANN

In this paper, the recognition information in aircraft images of Head-Up Display (HUD) was made using artificial neural network (ANN) and a correlation algorithm. During the flight tests, the images displayed on the HUD could be stored for later analysis. HUD images presents many aircraft data provi...

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Bibliographic Details
Main Authors: Guarino De Vasconcelos, Luiz Eduardo, Kusumoto, Andre Yoshimi, Paiva Oliveira Leite, Nelson, Moniz Araujo Lopes, Cristina
Format: Conference Proceeding
Language:English
Subjects:
Artificial neural networks
Biological neural networks
Character recognition
Flight Test
Head-Up Display
Image Processing
Image recognition
Neural Network
Neurons
Training
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Summary:In this paper, the recognition information in aircraft images of Head-Up Display (HUD) was made using artificial neural network (ANN) and a correlation algorithm. During the flight tests, the images displayed on the HUD could be stored for later analysis. HUD images presents many aircraft data provided by its avionics system (e.g. Altitude, feet, time). Therefore, HUD images are a primary source of information for most aircraft and pilots, especially in military missions. At IPEV (Flight Test" & Research Institute), the extraction of information from HUD images is performed manually, frame by frame, for later analysis. The big issue is that in one hour of flight test about 36,000 frames are generated. Therefore, data extraction becomes complex, time consuming and prone to failures. To reduce these problems, the IPEV developed an algorithm that load HUD images and then partitions the images in regions that were classified, recognized and converted into text by using ANN and a correlation algorithm. The development of the algorithm is presented in this paper.
DOI:10.1109/ITNG.2015.110