A Robust and Scalable Method for Infrared Target Identification
| Autor: | Luoyang Chen, Zheng Liu |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Pixel
business.industry Infrared Computer science Template matching ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 020206 networking & telecommunications Tracking system 02 engineering and technology Digital image processing Scalability 0202 electrical engineering electronic engineering information engineering General Earth and Planetary Sciences Entropy (information theory) 020201 artificial intelligence & image processing Computer vision Artificial intelligence business General Environmental Science |
| Zdroj: | Procedia Computer Science. 147:172-176 |
| ISSN: | 1877-0509 |
| DOI: | 10.1016/j.procs.2019.01.216 |
| Popis: | Recently, real-time and robust infrared target identification methodshave become critical for many applications in almost all kinds of modern weapon systems, including infrared search and tracking systems,surveillance systems and so on. However, at the long distance noises contaminated infrared imaging which the targets only occupied several pixels and the lowest entropy of information to obscure recognition the targets with digital image processing approaches effectively. To address these issues, a robust and scalable method for infrared target identification was proposed. With non-local and dynamic pattern recognition, the template matching accuracy between template and target improved significantly. It demonstrated that more than 80% accurate prediction rate of the proposed method in the practicing applications. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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