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Night Time and Low Visibility Driving Assistance Based on the Application of Colour and Geometrical Features Extraction

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9704))

Abstract

The present work shows an application to detect cars in night environments as a means to assist the car driving through HSV (Hue, Saturation, Value) colour extraction and geometric modelling. The developed algorithm has been implemented in smart devices through the platform Android. The detection and tracking of vehicles are implemented in low visibility environments such as night time, raining or snowing conditions; the different tests carried out confirm high performance rates of detection (p = 95.2 %). The information provided by the different sensors of the smart devices have been used to generate virtual information in a real driving environment (Augmented Reality) in order to complement the functionalities of the purposed solution. This information consists of visual, vibratory and auditory warnings that detect possible collisions and dangerous driving situations.

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Acknowledgment

This work was supported by Spanish National Plan for Scientific Technical Research and Innovation, project number TEC2013-48453-C2-2-R.

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Correspondence to Henry Cruz .

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© 2016 Springer International Publishing Switzerland

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Cruz, H., Meneses, J., Eckert, M., Martínez, J.F. (2016). Night Time and Low Visibility Driving Assistance Based on the Application of Colour and Geometrical Features Extraction. In: Alba, E., Chicano, F., Luque, G. (eds) Smart Cities. Smart-CT 2016. Lecture Notes in Computer Science(), vol 9704. Springer, Cham. https://doi.org/10.1007/978-3-319-39595-1_12

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  • DOI: https://doi.org/10.1007/978-3-319-39595-1_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-39594-4

  • Online ISBN: 978-3-319-39595-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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