Stop-sign recognition based on color/shape processing

Kehtarnavaz, Nasser; Griswold, Norman C.; Kang, Dae-Seong

doi:10.1007/bf01212298

Cited by 57 publications

(15 citation statements)

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“…w x Kehtarnavaz et al 4 have proposed an approach to stop sign recognition based on color segmentation followed by shape recognition using the Hough transform w x technique. Estevez and Kehtarnavaz 5 have presented a real-time approach to traffic sign recognition using color space relationships to segment red signs followed by a histographic mask for shape recognition.…”

Section: W Estevez and N Kehtarnavaz 50mentioning

confidence: 99%

Real-Time Object Specific Recognition via Raster Scan Video Processing

Estevez¹,

Kehtarnavaz²

1999

Real-Time Imaging

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Section: W Estevez and N Kehtarnavaz 50mentioning

confidence: 99%

Real-Time Object Specific Recognition via Raster Scan Video Processing

Estevez¹,

Kehtarnavaz²

1999

Real-Time Imaging

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“…Other researchers prefer working with spaces more immune to lighting changes. Although the HSI space is the most used [4,21,25,34], the Luv space has been also used [24].…”

Section: Sign Detectionmentioning

confidence: 99%

Traffic sign recognition and analysis for intelligent vehicles

Escalera

Armingol

Mata

2003

Image and Vision Computing

376

178

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This paper deals with object recognition in outdoor environments. In this type of environments, lighting conditions cannot be controlled and predicted, objects can be partially occluded, and their position and orientation is not known a priori. The chosen type of objects is traffic or road signs, due to their usefulness for sign maintenance, inventory in highways and cities, Driver Support Systems and Intelligent Autonomous Vehicles. A genetic algorithm is used for the detection step, allowing an invariance localisation to changes in position, scale, rotation, weather conditions, partial occlusion, and the presence of other objects of the same colour. A neural network achieves the classification. The global system not only recognises the traffic sign but also provides information about its condition or state. q

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“…Such as the United States, using color clustering method on the "stop" sign, developed ADIS system [4] with the correct identification of all the samples,but the system was not a real-time processing system taking a long time.…”

Section: ) Clustering Analysis Methodsmentioning

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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Stop-sign recognition based on color/shape processing

Cited by 57 publications

References 1 publication

Real-Time Object Specific Recognition via Raster Scan Video Processing

Real-Time Object Specific Recognition via Raster Scan Video Processing

Traffic sign recognition and analysis for intelligent vehicles

A Survey of Traffic Sign Recognition

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