A night time application for a real-time vehicle detection algorithm based on computer vision

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Abstract

Vehicle detection technology is the key technology of intelligent transportation systems, attracting the attention of many researchers. Although much literature has been published concerning daytime vehicle detection, little has been published concerning nighttime vehicle detection. In this study, a nighttime vehicle detection algorithm, consisting of headlight segmentation, headlight pairing and headlight tracking, is proposed. First, the pixels of the headlights are segmented in nighttime traffic images, through the use of the thresholding method. Then the pixels of the headlights are grouped and labeled, to analyze the characteristics of related components, such as area, location and size. Headlights are paired based on their location and size and then tracked via a tracking procedure designed to detect vehicles. Vehicles with only one headlight or those with three or four headlights are also detected. Experimental results show that the proposed algorithm is robust and effective in detecting vehicles in nighttime traffic.© Maxwell Scientific Organization, 2013.

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Zhou, S., Li, J., Shen, Z., & Ying, L. (2013). A night time application for a real-time vehicle detection algorithm based on computer vision. Research Journal of Applied Sciences, Engineering and Technology, 5(10), 3037–3043. https://doi.org/10.19026/rjaset.5.4620

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