Real-time automatic multi-style license plate detection in videos
| Autor: | Asmaa Elbamby, Mohamed Rehan, Elsayed E. Hemayed, Dina Helal |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
0209 industrial biotechnology
business.product_category business.industry Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 02 engineering and technology Function (mathematics) Tree (data structure) 020901 industrial engineering & automation Laptop 0202 electrical engineering electronic engineering information engineering Preprocessor 020201 artificial intelligence & image processing Computer vision Artificial intelligence business License |
| Zdroj: | 2016 12th International Computer Engineering Conference (ICENCO). |
| DOI: | 10.1109/icenco.2016.7856460 |
| Popis: | Despite License Plate Recognition is mainly regarded as a solved problem; most of the techniques have been mainly developed for specific country or special formats which can strictly limits their applicability. There have been extensive studies of license plate detection since the 70s. The suggested approaches have difficulties in processing high-resolution imagery in real-time. This paper presents a novel algorithm for real-time automatic multi-style license plate detection in videos. The proposed algorithm can detect in a real time multiple license plates with various sizes in unfamiliar and complex environment. In this system, candidate plate regions are extracted using a preprocessing function to increase accuracy while decreasing computational time. Then a tree of LBP-based cascade classifiers is used to classify the candidate plate regions into one of the learned style. The proposed approach has been applied to Egyptian license plates with four different plate styles. The proposed approach achieved a success rate of 94% at 25 frames/sec using a moderate laptop. |
| Databáze: | OpenAIRE |
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