A Vehicle Headlight and Taillight Detection Algorithm Based on Haar and Lab Color Features in Nighttime 


Vol. 45,  No. 5, pp. 842-846, May  2020
10.7840/kics.2020.45.5.842


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  Abstract

On-road vehicle detection is an important technique in Intelligent Transportation Systems. Under the daylight condition, the vehicle detection system can utilize the appearance information of vehicle such as color, shape, or typical vehicle patterns for vehicle detection with high performance. However, most of vehicle appearance features are insufficient and unstable in nighttime, and headlights or taillights become the reliable features for identifying vehicles. In this paper, a method for detecting both headlight and taillight regions during nighttime is proposed. At first, the Haar-like features using grayscale image and color feature using Lab color space are combined. Then, the Multi-Adaboost is trained with the combined features. The experimental results show the effectiveness of our method in detecting headlights and taillights at night.

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  Cite this article

[IEEE Style]

T. Pham and M. Yoo, "A Vehicle Headlight and Taillight Detection Algorithm Based on Haar and Lab Color Features in Nighttime," The Journal of Korean Institute of Communications and Information Sciences, vol. 45, no. 5, pp. 842-846, 2020. DOI: 10.7840/kics.2020.45.5.842.

[ACM Style]

Tuan-Anh Pham and Myungsik Yoo. 2020. A Vehicle Headlight and Taillight Detection Algorithm Based on Haar and Lab Color Features in Nighttime. The Journal of Korean Institute of Communications and Information Sciences, 45, 5, (2020), 842-846. DOI: 10.7840/kics.2020.45.5.842.

[KICS Style]

Tuan-Anh Pham and Myungsik Yoo, "A Vehicle Headlight and Taillight Detection Algorithm Based on Haar and Lab Color Features in Nighttime," The Journal of Korean Institute of Communications and Information Sciences, vol. 45, no. 5, pp. 842-846, 5. 2020. (https://doi.org/10.7840/kics.2020.45.5.842)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880