Search results for "Road sign"

showing 6 items of 6 documents

La standardizzazione dei segnali stradali di pericolo nell’unione Europea

2015

The aim of this research is to find a solution for the standardization of road signs in the EU zone by a comparative analysis of different national sign systems to establish a common set from a single country. This work is based on the idea that road sign standardization might increase the safety level of transnational journeys and foster the relationships among the various members of the EU Community. This paper presents the outcome of the first step of the research, which focuses on the harmonization of danger signs. In more detail, a multicriteria approach is applied to rank 19 EU Member States on the basis of three main aspects: the installation cost of new signs, new sign learning issu…

Multicriteria analysiSettore ICAR/05 - TrasportiVisual perceptionGraphical analysiRoad sign
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Standardization of Road Danger Signs in the European Union

2015

The aim of this research is to find a solution for the standardization of road signs in the EU zone by a comparative analysis of different national sign systems to establish a common set from a single country. This work is based on the idea that road sign standardization might increase the safety level of transnational journeys and foster the relationships among the various members of the EU Community. This paper presents the outcome of the first step of the research, which focuses on the harmonization of danger signs. In more detail, a multicriteria approach is applied to rank 19 EU Member States on the basis of three main aspects: the installation cost of new signs, new sign learning issu…

road signsEngineeringmulticriteria analysisStandardizationOperations researchbusiness.industryRank (computer programming)lcsh:TA1001-1280Sign (semiotics)visual perceptionOcean EngineeringHarmonizationDanger signgraphical analysisWork (electrical)Risk analysis (engineering)road signs; multicriteria analysis; graphical analysis; visual perceptionmedia_common.cataloged_instancelcsh:Transportation engineeringEuropean unionbusinessSet (psychology)Engineering (miscellaneous)Civil and Structural Engineeringmedia_commonPROMET - Traffic&Transportation
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Improved Traffic Signal Detection and Classification via Image Processing Algorithms

2012

An image analysis technique for automatic traffic sign detection and classification is proposed. This analysis makes it possible, after proper training, to detect, recognize and classify vertical road signs from video frames acquired on a moving vehicle equipped with cameras, as well as to identify anomalies with respect to road sign regulations (positioning and visibility). The experimental results show that this technique allows one to correctly detect and classify almost all vertical signs and, mainly in extra-urban environment, it can be considered as highly reliable, apart from being really versatile and user-friendly for road inventory and road maintenance purposes.

EngineeringMaintenancebusiness.industryPoison controlRoad signalTraffic sign detectionImage (mathematics)Traffic signalDigital image processingSettore ICAR/04 - Strade Ferrovie Ed AeroportiAutomatic detectionTracking and classificationGeneral Materials ScienceComputer visionArtificial intelligencebusinessVisibilityMoving vehicleSimulationSign (mathematics)Procedia - Social and Behavioral Sciences
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ROBUST ROAD SIGNS SEGMENTATION IN COLOR IMAGES

2012

International audience; This paper presents an efficient method for road signs segmentation in color images. Color segmentation of road signs is a difficult task due to variations in the image acquisition conditions. Therefore, a color constancy algorithm is usually applied prior to segmentation, which increases the computation time. The proposed method is based on a log-chromaticity color space which shows good invariance properties to changing illumination. Thus, the method is simple and fast since it does not require color constancy algorithms. Experiments with a large dataset and comparison with other approaches, show the robustness and accuracy of the method in detecting road signs in …

[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Color segmentationRoad sign detectionLog-chromaticity color space.ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Log-chromaticity color space[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Color constancy
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Ottimizzazione delle prestazioni di una rete stradale tramite l’unificazione del sistema della segnaletica

2010

L’argomento principale di questa tesi si manifesta nella soddisfazione della necessità di armonizzare la segnaletica stradale verticale europea, definendo una strategia di minimizzazione dei costi di sostituzione complessivi della cartellonistica non uniforme, per contribuire a migliorare i livelli di sicurezza e di soddisfacimento dell’utenza dell’infrastruttura stradale. Una maggiore uniformità della segnaletica stradale permetterebbe ai conducenti impegnati nei traffici transfrontalieri su gomma di dover recepire un minor carico di informazioni visive, facendo riferimento ad un numero minore di segnali stradali, in quanto armonizzati con quelli dei loro paesi di provenienza. Altro scopo …

Settore ICAR/05 - TrasportiSegnali stradali armonizzazione della segnaletica modello di riconoscimento dei segnali stradaliroad signs harmonization recognition model
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Road Signs Detection and Reconstruction using Gielis Curves

2012

International audience; Road signs are among the most important navigation tools in transportation systems. The identification of road signs in images is usually based on first detecting road signs location using color and shape information. In this paper, we introduce such a two-stage detection method. Road signs are located in images based on color segmentation, and their corresponding shape is retrieved using a unified shape representation based on Gielis curves. The contribution of our approach is the shape reconstruction method which permits to detect any common road sign shape, i.e. circle, triangle, rectangle and octagon, by a single algorithm without any training phase. Experimental…

[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Gielis curves.Color segmentationRoad sign detectionGielis curves[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Contour fitting
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