Brazilian License Plate Detection Using Histogram of Oriented Gradients and Sliding Windows
This work addresses license plate detection for traffic management applications in Brazil, but it is incremental as it adapts an existing method to a new regional context.
The paper tackled the problem of Brazilian license plate detection for automatic traffic monitoring by applying a sliding window approach with Histogram of Oriented Gradients (HOG) features, achieving a recall higher than 98% and precision higher than 78% on a public dataset.
Due to the increasingly need for automatic traffic monitoring, vehicle license plate detection is of high interest to perform automatic toll collection, traffic law enforcement, parking lot access control, among others. In this paper, a sliding window approach based on Histogram of Oriented Gradients (HOG) features is used for Brazilian license plate detection. This approach consists in scanning the whole image in a multiscale fashion such that the license plate is located precisely. The main contribution of this work consists in a deep study of the best setup for HOG descriptors on the detection of Brazilian license plates, in which HOG have never been applied before. We also demonstrate the reliability of this method ensured by a recall higher than 98% (with a precision higher than 78%) in a publicly available data set.