Home // MMEDIA 2013, The Fifth International Conferences on Advances in Multimedia // View article

Quantistic approach for classification of images

Authors:
Federico F. Barresi
Giuseppe Battista
Jacopo Pellegrino
Walter Allasia

Keywords: traffic sign recognition; automatic video processing; image deterioration; Kullback-Leibler divergence; Kolmogorov- Smirnov statistical test

Abstract:
This paper describes a software application based on statistical methods for the automatic recognition of traffic sign deterioration. The evaluation of traffic sign degradation is usually performed by devices applied on top of the road sign surface, measuring color parameters such as chromatic coordinates and the luminance factor. Moreover, the devices can only check a small fraction of the traffic sign surface at a time, requiring several acquisitions on the same traffic sign. In order to reduce the costs related to monitoring and have a periodic control of the traffic sign status, we propose a fast automatic method based on video acquisition and processing that can be easily operated in patrolling vehicles provided with a camera. A pattern detection algorithm based on color and texture features is applied to the images extracted from the acquired videos in order to detect the traffic signs ROIs, which are analyzed using a statistical approach based on the Kullback-Leibler divergence and Kolmogorov-Smirnov test. Making use of a control sample of not deteriorated traffic sign images, a comparison between the acquired and the reference images is performed. Both statistical methods have been used to compare 150 pairs of traffic signs, achieving high precision and recall, proving that the proposed approach can be a good candidate solution for automatic traffic sign deterioration analysis.

Pages: 7 to 11

Copyright: Copyright (c) IARIA, 2013

Publication date: April 21, 2013

Published in: conference

ISSN: 2308-4448

ISBN: 978-1-61208-265-3

Location: Venice, Italy

Dates: from April 21, 2013 to April 26, 2013