Abstract
Weather recognition is widely required in many areas, and it is also a challenging and brand-new subject. This paper proposes an approach to recognize weather based on images captured by in-vehicle vision system. We bring three groups of features, including histogram of gradient amplitude, HSV color histogram, road information, and employ an algorithm based on Real AdaBoost, making use of the category structure to achieve the task of classification. Experiments confirm superior performances on our dataset collected from images captured by vision system.
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Yan, X., Luo, Y., Zheng, X. (2009). Weather Recognition Based on Images Captured by Vision System in Vehicle. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5553. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01513-7_42
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DOI: https://doi.org/10.1007/978-3-642-01513-7_42
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-01512-0
Online ISBN: 978-3-642-01513-7
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