Robust method for road sign detection and recognition

Piccioli, G.; Micheli, Enrico De; Parodi, Pietro; Campani, M.

doi:10.1016/0262-8856(95)01057-2

Cited by 238 publications

(119 citation statements)

References 5 publications

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“…It is difficult to adapt to the actual reality in the environment recognition. In 2000, Japan Osaka University developed a active vision system that can recognize speed sign and text [7] , detecting by threshold segmentation, recognizing using template matching method.…”

Section: ) Matching Based On Pixel Levelmentioning

confidence: 99%

A Survey of Traffic Sign Recognition

Zhong¹,

Yu²,

Zhang³

2015

Proceedings of the International Conference on Logistics, Engineering, Management and Computer Science

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Abstract-As the main component of intelligent transportation systems, Traffic sign recognition system has been extensively studied in intelligent vehicles, military and unmanned vehicles and other projects. In this paper, firstly, it briefly introduced the traffic sign recognition research status and development background, and then according to different recognition review,it mainstreamd traffic sign recognition method, through comparative analysis of various methods,it summarized the in traffic sign recognition, and prospected the future direction of development.

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Section: ) Matching Based On Pixel Levelmentioning

confidence: 99%

A Survey of Traffic Sign Recognition

Zhong¹,

Yu²,

Zhang³

2015

Proceedings of the International Conference on Logistics, Engineering, Management and Computer Science

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“…Ce traitement traite une image en 1 à 2 secondes, et est intégré dans un système de poursuite et de reconnaissance, mais les résultats ne sont présentés que sous la forme d'illustrations. La détection de limitation de vitesse est aussi assurée par une transformée de Hough par (Miura et al, 2000) (Piccioli et al, 1996), des régions d'intérêt sont sélectionnées en s'appuyant sur un seuillage dans le plan Hue-Saturation de HSV. Des polygones sont ajustés aux chaînes de contours linéaires, et sous l'hypothèse que les triangles ne sont ni inclinés, ni distordus par la perspective, des triangles équilatéraux avec un côté horizontal et deux côtés de pente égale à ±π/3 radians sont recherchés.…”

Section: Les Méthodes De Détection De Panneauxunclassified

Détection des panneaux de signalisation routière par accumulation bivariée

Belaroussi¹,

Tarel²

2010

Traitement du signal

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RÉSUMÉ. Nous présentons une méthode géométrique utilisant l'orientation du gradient pour la détection de la signalisation verticale dans des images fixes, indépendamment de leur position et de leur orientation. La détection est réalisée par une transformation de type accumulateur de Hough bivariée, fondée sur l'utilisation de paires de points avec des contraintes sur leurs gradients. Les panneaux circulaires et polygonaux (non triangulaires) sont détectés par la transformation chinoise bilatérale TCB. Cette transformation est rapide et ne fait pas de distinction entre les cercles et les polygones 4 côtés ou plus. Le cas des panneaux triangulaires est traité par la transformation en sommet et bissectrice TSB, capable de détecter précisemment les bissectrices et les sommets d'un triangle. Les performances de la TCB et de la TSB sont estimées sur plusieurs bases d'images de scènes urbaines.ABSTRACT. We present a real-time approach for circular and polygonal road signs detection in still images, regardless of their pose and orientation. Object detection is performed using a Hough like transform based on accumulation on pairs of points with their gradients. Circular and polygonal (non triangular) traffic signs are detected by the so-called Bilateral Chinese Transform BCT. Triangular traffic signs are processed by the Vertex Bisector Transform VBT. These two approaches are tested on several databases of urban scene.MOTS-CLÉS : transformation en symétrie généralisée, transformation en symétrie pour les coins, transformation en sommet et bissectrice, transformation chinoise, contours orientés, panneaux routiers, temps réel, transformée de Hough. Extended abstractRoad sign identification in images is an important issue, especially for vehicle safety and road management 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 article on the first stage of the process, namely road sign detection. We focus our work on a feature-based approach to build geometrical models of various kind of shapes : triangle on the one hand, square, diamond, octagon and circle on the other hand.We introduce two cumulative bivariate transformations :-the Bilateral Chinese Transform BCT, tailored for the detection of circular and polygonal road signs with four or more sides.-The Vertex and Bisector Transformation VBT, dedicated to the detection of triangular traffic signs.In the BCT approach (Belaroussi et al., 2009b), object detection is done using a pairwise gradient-based symmetry transform able to detect circles and polygons indistinctly. The BCT seeks the symmetry of shape in the gradient orientation : it decomposes an object into a set of parallel contours with opposite gradients, and models this gradient field symmetry using an accumulation of radial symmetry evidences. Figure 7 illustrates the signed accumulators obtained with the BCT over two elliptical shapes : it is worth noticing that the BCT is also orientation free....

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“…Three color image histograms ( Fig. 2) are analyzed to find a point with a sufficient number of colored pixels, of the 3 interested colors, on the same row and also on the same column [12].…”

Section: Color Segmentationmentioning

confidence: 99%

Automatic Recognition of Road Sign Passo-Carrabile

Lombardi

Marmo

Toccalini

2005

Image Analysis and Processing – ICIAP 2005

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Abstract. This paper describes a method to detect and identify the typical italian road sign passo-carrabile. The system first determines the region of interest within the image, using color segmentation, then the signal of no waiting is identified using shape and color information, and finally the text label passo-carrabile is recognised with a state diagram and a set of specific tests on the shape of the words. The obtained results show the feasibility of the system.

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Robust method for road sign detection and recognition

Cited by 238 publications

References 5 publications

A Survey of Traffic Sign Recognition

A Survey of Traffic Sign Recognition

Détection des panneaux de signalisation routière par accumulation bivariée

Automatic Recognition of Road Sign Passo-Carrabile

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