Anzeige
Erschienen in:
2006 | OriginalPaper | Buchkapitel
A Discontinuity Adaptive Method for Super-Resolution of License Plates
verfasst von : K. V. Suresh, A. N. Rajagopalan
Erschienen in: Computer Vision, Graphics and Image Processing
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
In this paper, a super-resolution algorithm tailored to enhance license plate numbers of moving vehicles in real traffic videos is proposed. The algorithm uses the information available from multiple, sub-pixel shifted, and noisy low-resolution observations to reconstruct a high-resolution image of the number plate. The image to be super-resolved is modeled as a Markov random field and is estimated from the low-resolution observations by a graduated non-convexity optimization procedure. To preserve edges in the reconstructed number plate for better readability, a discontinuity adaptive regularizer is proposed. Experimental results are given on several real traffic sequences to demonstrate the edge preserving capability of the proposed method and its robustness to potential errors in motion and blur estimates. The method is computationally efficient as all operations are implemented locally in the image domain.