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http://dx.doi.org/10.7840/kics.2016.41.12.1978

Robust vehicle Detection in Rainy Situation with Adaboost Using CLAHE  

Kang, Seokjun (Kyungpook National University Department of Electronics Engineering)
Han, Dong Seog (Kyungpook National University Department of Electronics Engineering)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.41, no.12, 2016 , pp. 1978-1984 More about this Journal
Abstract
This paper proposes a robust vehicle detecting method by using Adaboost and CLAHE(Contrast-Limit Adaptive Histogram Equalization). We propose two method to detect vehicle effectively. First, we are able to judge rainy and night by converting RGB value to brightness. Second, we can detect a taillight, designate a ROI(Region Of Interest) by using CLAHE. And then, we choose an Adaboost algorithm by comparing traditional vehicle detecting method such as GMM(Gaussian Mixture Model), Optical flow and Adaboost. In this paper, we use proposed method and get better performance of detecting vehicle. The precision and recall score of proposed method are 0.85 and 0.87. That scores are better than GMM and optical flow.
Keywords
CLAHE; ROI Extraction; Vehicle Detection; Image Processing; Adaboost;
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Times Cited By KSCI : 3  (Citation Analysis)
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