Feature extraction for classification of different weather conditions

doi:10.1007/s11460-011-0151-1

Front Elect Electr Eng Chin

2011, Vol. 6

Issue (2) : 339-346 https://doi.org/10.1007/s11460-011-0151-1

RESEARCH ARTICLE

Feature extraction for classification of different weather conditions

Xudong ZHAO(

), Peng LIU, Jiafeng LIU, Xianglong TANG

School of Computer Science, Harbin Institute of Technology, Harbin 150001, China

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Abstract

Classification of different weather conditions provides a first step support for outdoor scene modeling, which is a core component in many different applications of outdoor video analysis and computer vision. Features derived from intrinsic properties of the visual effects of different weather conditions contribute to successful classification. In this paper, features representing both the autocorrelation of pixel-wise intensities over time and the max directional length of rain streaks or snowflakes are proposed. Based on the autocorrelation of each pixel’s intensities over time, two temporal features are used for coarse classification of weather conditions according to their visual effects. On the other hand, features are extracted for fine classification of video clips with rain and snow. The classification results on 249 video clips associated with different weather conditions indicate the effectiveness of the extracted features, by using C-SVM as the classifier.

Keywords feature extraction classification rain snow illumination variation weather condition autocorrelation function

Corresponding Author(s): ZHAO Xudong,Email:percydd@163.com

Issue Date: 05 June 2011

Cite this article:

Peng LIU,Jiafeng LIU,Xianglong TANG, et al. Feature extraction for classification of different weather conditions[J]. Front Elect Electr Eng Chin, 2011, 6(2): 339-346.

URL:

https://academic.hep.com.cn/fee/EN/10.1007/s11460-011-0151-1
https://academic.hep.com.cn/fee/EN/Y2011/V6/I2/339

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