Learning to Decipher License Plates in Severely Degraded Images
| Autor: | Franziska Schirrmacher, Paula Kaiser, Benedikt Lorch, Christian Riess |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
050210 logistics & transportation
Image quality Computer science business.industry Low resolution Deep learning 05 social sciences 02 engineering and technology Convolutional neural network Image degradation 0502 economics and business 0202 electrical engineering electronic engineering information engineering DECIPHER 020201 artificial intelligence & image processing Computer vision Artificial intelligence Organised crime business License |
| Zdroj: | Pattern Recognition. ICPR International Workshops and Challenges ISBN: 9783030687793 ICPR Workshops (6) |
| Popis: | License plate recognition is instrumental in many forensic investigations involving organized crime and gang crime, burglaries and trafficking of illicit goods or persons. After an incident, recordings are collected by police officers from cameras in-the-wild at gas stations or public facilities. In such an uncontrolled environment, a generally low image quality and strong compression oftentimes make it impossible to read license plates. Recent works showed that characters from US license plates can be reconstructed from noisy, low resolution pictures using convolutional neural networks (CNN). However, these studies do not involve compression, which is arguably the most prevalent image degradation in real investigations. |
| Databáze: | OpenAIRE |
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