Article

Automatic evaluation of traffic sign visibility using SVM recognition methods

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Abstract

http://www.uah.es Abstract: We present an automated low cost method for evaluating the visibility of traffic signs. For this propose we define a parameter which evaluates how road signs are seen by drivers at night. Thus, the evaluation is done from inside a vehicle, using the headlamps as light sources and a colour digital camera to capture the signs in sequences acquired as we approach them. The captured frames are then automatically processed with a software which allows us to detect and recognize the signs using Support Vector Machines (SVM) as a novel classification technique. Finally, a parameter for measuring the visibility of signs is obtained from the sequence. As example, this technique has been applied successfully over three different signs with three different degrees of surface deterioration.

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... Therefore, it is dangerous to directly control the information only with the information from a driver's gaze. Another approach is based on the target's visibility estimated with an in-vehicle camera [3]- [5]. In particular, the visibility of a traffic sign changes largely depending on the environmental conditions despite its great importance in a traffic scene. ...
... For practical use, some research groups including the authors themselves have proposed methods to estimate the visibility of a traffic sign with an in-vehicle camera [3], [4], [6]. Siegmann's model [3] calculates the visibility level based on only luminance, and visual properties of humans are not considered adequately. ...
... For practical use, some research groups including the authors themselves have proposed methods to estimate the visibility of a traffic sign with an in-vehicle camera [3], [4], [6]. Siegmann's model [3] calculates the visibility level based on only luminance, and visual properties of humans are not considered adequately. Simon's model [4] learns a massive number of appearances of a target traffic sign in advance. ...
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