Deep Learning Based Segmentation Free License Plate Recognition Using Roadway Surveillance Camera Images
This work addresses the need for accurate license plate recognition in smart traffic enforcement systems, though it appears incremental as it adapts existing deep learning techniques to a specific domain.
The authors tackled the problem of license plate recognition from low-resolution roadway surveillance camera images by proposing a segmentation-free deep learning method, achieving high accuracy on a test set of 2000 images.
Smart automated traffic enforcement solutions have been gaining popularity in recent years. These solutions are ubiquitously used for seat-belt violation detection, red-light violation detection and speed violation detection purposes. Highly accurate license plate recognition is an indispensable part of these systems. However, general license plate recognition systems require high resolution images for high performance. In this study, we propose a novel license plate recognition method for general roadway surveillance cameras. Proposed segmentation free license plate recognition algorithm utilizes deep learning based object detection techniques in the character detection and recognition process. Proposed method has been tested on 2000 images captured on a roadway.