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Author Belaroussi, R. ♦ Foucher, P. ♦ Tarel, J. -P. ♦ Soheilian, B. ♦ Charbonnier, P. ♦ Paparoditis, N.
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Road Sign Detection ♦ Case Study ♦ Road Sign ♦ Radial Symmetry Transform ♦ Road Sign Identification ♦ Complex Urban Scene ♦ Contour Fitting ♦ Pair-wise Voting Scheme ♦ Different Shape ♦ Important Issue ♦ Ground-truth Image Database ♦ Edge Information ♦ Different State-of-the-art Approach ♦ First Stage ♦ Test Dataset ♦ Vehicle Safety Application ♦ Fr Benchmarking ♦ Geometrical Model ♦ New Research Perspective
Abstract Road sign identification in images is an important issue, in particular for vehicle safety applications. It is usually tackled in three stages: detection, recognition and tracking, and evaluated as a whole. To progress towards better algorithms, we focus in this paper on the first stage of the process, namely road sign detection. More specifically, we compare, on the same ground-truth image database, results obtained by three algorithms that sample different state-of-the-art approaches. The three tested algorithms: Contour Fitting, Radial Symmetry Transform, and pair-wise voting scheme, all use color and edge information and are based on geometrical models of road signs. The test dataset is made of 847 images 960 × 1080 of complex urban scenes (available at www.itowns.fr/benchmarking.html). They feature 251 road signs of different shapes (circular, rectangular, triangular), sizes and types. The pros and cons of the three algorithms are discussed, allowing to draw new research perspectives. 1.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article