A Method of Weather Recognition based on Outdoor Images

Qian Li, Yi Kong, Shi-ming Xia

Abstract

To improve the quality of video surveillance in outdoor and automatic acquire of the weather situations, a method to recognize weather phenomenon based on outdoor images is presented. There are three features of our method: firstly, the features, such as the power spectrum slope, contrast, noise and saturation and so on are extracted, after analysing the effect of weather situations on image; secondly, a decision tree is constructed in accordance with the distance between the features; thirdly, when every SVM classifier on the non-leaf node of the decision tree is constructed, some features are selected by assigning the weight. The experiment results prove that the proposed method can effectively recognize the weather situations in outdoor.

References

  1. Bossu J., Hautiere N., Tarel J. Rain or snow detection in image sequences through use of a Histogram of Orientation of streaks. International Journal of Computer Vision. 2011, vol. 93(3): 348-367.
  2. Burton G., Moorhead I., 1987. Color and spatial structure in natural scenes. Applied Optics. vol. 26: 157-160.
  3. Garg, K., Nayar, Shree K., 2004. Detection and removal of rain from videos. IEEE Conference on Computer Vision and Pattern Recognition 2004, vol. 1:528-535.
  4. Lagorio A., Grosso E., 2008. Automatic detection of adverse weather situations in traffic scenes” IEEE Fifth International Conference on Advanced Video and Signal Based Surveillance, pp. 273-279.
  5. Liang S., Sun Z., 2008. Sketch retrieval and relevance feedback with biased SVM classification. Pattern Recognition Letters. vol. 29:1733-1741.
  6. Liu R., Li Z., Jia J., 2008. Image partial blur detection and classification. IEEE Conference on In Computer Vision and Patern Recognition, pp. 1-8.
  7. Narasimhan, Srinivasa G., Nayar, Shree K., 2002. Vision and the atmosphere. International Journal of Computer Vision, 48(3): 233-254.
  8. Narasimhan, S., Nayar, S.. Contrast restoration of weather degraded images. IEEE Trans. Pattern Analysis and Machine, 2003:713-724.
  9. Peli Eli, 1990. Contrast in complex images. Journal of the Optical Society of America, vol. 7: 2032-2040.
  10. Roser M., Moosmann F., 2008. Classification of weather situations on single color images. IEEE Intelligent Vehicles Symposium, pp. 798-803.
  11. Shen L., Tan P. Photometric stereo and weather estimation using internet images. 2009 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009, pp. 1850-1857.
  12. Tai S., Yang S., 2008. A fast method for image noise estimation using laplacian operator and adaptive edge detection. Commnications, Control and Signal Processing, pp. 1077-1081.
  13. Takahashi F., Abe S., 2002. Decision-tree-based multiclass support vector machines. Neural Information Processing, ICONIP 2002, vol.3: 1418- 1422.
  14. Yan X., Luo Y., Zheng X., 2009. Weather recognition based on images captured by vision system in vehicle. Proceedings of the 6th International Symposium on Neural Network: Advance in Neural Networks, vol 3:390-398.
Download


Paper Citation


in Harvard Style

Li Q., Kong Y. and Xia S. (2014). A Method of Weather Recognition based on Outdoor Images . In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2014) ISBN 978-989-758-004-8, pages 510-516. DOI: 10.5220/0004724005100516


in Bibtex Style

@conference{visapp14,
author={Qian Li and Yi Kong and Shi-ming Xia},
title={A Method of Weather Recognition based on Outdoor Images},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2014)},
year={2014},
pages={510-516},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004724005100516},
isbn={978-989-758-004-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2014)
TI - A Method of Weather Recognition based on Outdoor Images
SN - 978-989-758-004-8
AU - Li Q.
AU - Kong Y.
AU - Xia S.
PY - 2014
SP - 510
EP - 516
DO - 10.5220/0004724005100516