Automated Extraction Information System from HUDs Images Using ANN
| Autor: | Cristina Moniz Araujo Lopes, André Yoshimi Kusumoto, Luiz Eduardo Guarino de Vasconcelos, Nelson Paiva Oliveira Leite |
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| Rok vydání: | 2015 |
| Předmět: |
Head-up display
Contextual image classification Computer science business.industry Frame (networking) ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ComputerApplications_COMPUTERSINOTHERSYSTEMS Image processing Avionics computer.software_genre Flight test law.invention Information extraction law Computer vision Artificial intelligence business Image retrieval computer |
| Zdroj: | 2015 12th International Conference on Information Technology - New Generations. |
| Popis: | 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" a 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. |
| Databáze: | OpenAIRE |
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