Traffic Sign Recognition Based On Color Image Evaluationion

Priese, Lutz; Rehrmann, Volker; Schian, R.; Lakmann, Raimund

doi:10.1109/ivs.1993.697304

Cited by 32 publications

(13 citation statements)

References 4 publications

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“…Most researchers segment signs according to their shapes, such as red circular objects for red signs [2,3,7,10,11] or rectangular objects for highway signs [1]. In blue traffic signs, same arrow patterns are used in rectangular and circular signs to indicate the same meaning which is to limit the permission of using the road to the direction designated by the sign.…”

Section: Criteria Of Sign Candidatementioning

confidence: 99%

“…They dealt with two patterns of arrows. Other researchers used different algorithms like color region and color structure code in a hierarchical growing method and applied convex hull for shape detection on still images including red and blue signs [2,3]. Methods based on the function of foveal vision [4], haar wavelet, Bayesian and AdaBoost patches algorithms were proposed [5].…”

Section: Introductionmentioning

confidence: 99%

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Real-Time Recognition of Blue Traffic Signs Designating Directions

Alsibai

Hirai

2010

Int. J. ITS Res.

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In this research we propose a real-time system to recognize blue traffic signs designating directions. This research is complementary to the previous work done on six annular red signs. The system consists of several processing steps: We firstly label the blue objects in each frame and segment them from the background. After that we try to verify if the segmented blue object is a sign candidate, and then we segment white objects within the blue object. Finally we classify the white objects by matching them to arrow patterns according to geometrical features, or reject them if no arrow pattern is matched. Classification is done using a decision tree. Processing time is about 110 ms/frame, and recognition rate is about 81%.

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Section: Criteria Of Sign Candidatementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Real-Time Recognition of Blue Traffic Signs Designating Directions

Alsibai

Hirai

2010

Int. J. ITS Res.

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“…speed limitation signs) [1], [2] and systems working on almost the complete set of signs ( [3], [4], [5], [6], [7] the last two related with Italian and Spanish traffic signs).…”

Section: Introductionmentioning

confidence: 99%

A validation tool for traffic signs recognition systems

Marenco

Fontana

Ghisio

et al. 2009

2009 12th International IEEE Conference on Intelligent Transportation Systems

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Abstract-During the last few years many Advanced Driver Assistant Systems have been developed and a larger number of new car models every year is going to be equipped with these systems. However the product/function scenario lacks of common evaluation methodologies and tools for testing and improving performances of these systems. In this paper a validation methodology and a tool for Traffic Sign Recognition Systems evaluation (TSRs) is described.

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“…The most common method used for traffic signs detection is colour-segmentation. This method is based on the assumed fact that the wavelength coming from a sign, for instance the redcoloured edge of a speed-limit sign, does not change with changes in the intensity and the incidence-angle of the light onto the sign, if HSV or HIS spaces are used [4], [5]. The image of the camera is not, however, completely invariant under changes in the chromaticity of the received light, being these changes due to shades, adverse weather conditions, etc.…”

Section: Introductionmentioning

confidence: 99%

Fast Road Sign Detection Using Hough Transform for Assisted Driving of Road Vehicles

García-Garrido

Sotelo

Martín-Gorostiza

2005

Lecture Notes in Computer Science

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Abstract.A system for real-time traffic sign detection is described in this paper. The system uses restricted Hough transform for circumferences in order to detect circular signs, and for straight lines for triangular ones. Some results obtained from a set of real road images captured under both normal and adverse weather conditions are presented as well in order to illustrate the robustness of the detection system. The average processing time is 30 ms per frame, what makes the system a good approach to work in real time conditions.

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Traffic Sign Recognition Based On Color Image Evaluationion

Cited by 32 publications

References 4 publications

Real-Time Recognition of Blue Traffic Signs Designating Directions

Real-Time Recognition of Blue Traffic Signs Designating Directions

A validation tool for traffic signs recognition systems

Fast Road Sign Detection Using Hough Transform for Assisted Driving of Road Vehicles

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