Adaptive Weighted Morphology Tree Classifier for Aircraft Type Recognition
Zhigang Liu, Yanying Guo
Available Online October 2016.
- https://doi.org/10.2991/ceie-16.2017.89How to use a DOI?
- Aircraft Type Recognition; Adaptive Weighted Morphology; Tree Classifier; Least Distance; Auto-docking System
- Aircraft type recognition is a problem and key factor of safe docking of aircraft in airport auto-docking guide system. Based on adaptive weighted morphology tree classifier algorithm, it is approved for aircraft type recognition to solve the key issues to docking guide, useing image analysis and recognition technology to complete the type discrimination, so as to overcome the shortcomings of the aircraft in the whole range of berth travel and improve the speed and reliability of the search. According to the feature of target size and feature change during the process of aircraft movement, the adaptive weight morphological algorithm extracts the invariant features, which can solve the problem of feature transform of aircraft type recognition. The experimental results indicate that the effectiveness of the current recognition system is given. The system provides a good performance in aircraft recognition and offers better robustness against noise and poor image quality, which can satisfy the auto-docking system requirements of high precision, rapid speed and stabilization.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Zhigang Liu AU - Yanying Guo PY - 2016/10 DA - 2016/10 TI - Adaptive Weighted Morphology Tree Classifier for Aircraft Type Recognition BT - Proceedings of the International Conference on Communication and Electronic Information Engineering (CEIE 2016) PB - Atlantis Press SP - 696 EP - 701 SN - 2352-5401 UR - https://doi.org/10.2991/ceie-16.2017.89 DO - https://doi.org/10.2991/ceie-16.2017.89 ID - Liu2016/10 ER -