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Real-Time Traffic Light Signal Recognition System for a Self-driving Car

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Advances in Signal Processing and Intelligent Recognition Systems (SIRS 2017)

Abstract

In this paper, the implementation of image recognition for traffic light signal recognition system is demonstrated. The detection of traffic light signal is an essential step for a self-driving car. Here we present a method for the recognition of traffic lights using image processing and controlling the vehicle accordingly. The algorithm developed in this research work is tested and processed using a Raspberry Pi board. The input-output modules such as camera, motors and chassis of the model car are all integrated together so they can perform as a single unit. For processing the image on real-time, OpenCV is used as an API to perform essential steps in the detection of signal like capturing, resizing, thresholding and morphological operations. Contour detection on a binary image has further been used for object detection. The algorithm has been tested with Valgrind profiling tools Callgrind and Cachegrind.

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Correspondence to Nakul Agarwal .

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Agarwal, N., Sharma, A., Chang, J.R. (2018). Real-Time Traffic Light Signal Recognition System for a Self-driving Car. In: Thampi, S., Krishnan, S., Corchado Rodriguez, J., Das, S., Wozniak, M., Al-Jumeily, D. (eds) Advances in Signal Processing and Intelligent Recognition Systems. SIRS 2017. Advances in Intelligent Systems and Computing, vol 678. Springer, Cham. https://doi.org/10.1007/978-3-319-67934-1_24

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  • DOI: https://doi.org/10.1007/978-3-319-67934-1_24

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