Abstract：To improve the quality of video surveillance outdoors and to automatically acquire the weather situations, a method to recognize weather situations in outdoor images is presented. It extracted such parameters as power spectrum slope, contrast, noise, saturation as features to realize the multi-classification of weather situations with Support Vector Machine (SVM). Then a decision tree was constructed in accordance with the distance between these features. The experimental results on WILD image base and our image set of eight hundred samples show that the proposed method can recognize sunny, overcast, foggy weather more than 85%, and recognize rainy weather more than 75%.
李骞 范茵 张璟 李宝强. 基于室外图像的天气现象识别方法[J]. 计算机应用, 2011, 31(06): 1624-1627.
Li Qian FAN Yin ZHANG Jing LI BAOqiang. Method of weather recognition based on decision-tree-based SVM. Journal of Computer Applications, 2011, 31(06): 1624-1627.
2011, Vol. 31 
