Superresolution of license plates in real traffic videos
| Autor: | K. V. Suresh, A. N. Rajagopalan, G.M. Kumar |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2007 |
| Předmět: |
Intelligent control
Optimization Markov random field (MRF) Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Markov process Image processing Markov model Superresolution License plates (automobile) symbols.namesake Image resolution Robustness (computer science) Computer vision Gibbs distribution (GD) Markov random field License plate text business.industry Mechanical Engineering Markov processes Sensor fusion Subpixel rendering Computer Science Applications Video signal processing Automotive Engineering Graduated nonconvexity (GNC) Image enhancement symbols Artificial intelligence Intelligent transport system business |
| Zdroj: | IndraStra Global. |
| ISSN: | 2381-3652 |
| DOI: | 10.1109/TITS.2007.895291 |
| Popis: | In this paper, a novel method to enhance license plate numbers of moving vehicles in real traffic videos is proposed. A high-resolution image of the number plate is obtained by fusing the information derived from multiple, subpixel shifted, and noisy low-resolution observations. The image to be superresolved is modeled as a Markov random field and is estimated from the observations by a graduated nonconvexity optimization procedure. A discontinuity adaptive regularizer is used to preserve the edges in the reconstructed number plate for improved readability. Experimental results are given on several traffic sequences to demonstrate the robustness of the proposed method to potential errors in motion and blur estimates. The method is computationally efficient as all operations can be implemented locally in the image domain. � 2007 IEEE. |
| Databáze: | OpenAIRE |
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