Snowfall Detection Under Bad Visibility Scene

An effect of weather is very critical in outdoor camera surveillance applications. So, the authors focus on bad weather by snow and propose an algorithm of detecting snowfall from surveillance camera images. The proposed algorithm increases a contrast of an image by haze removal. A contrast of hazy image is reduced by haze color of atmosphere. When several haze colors exist in an image, the degree of contrast degradation is different for each haze color. To deal with this problem, the proposed method performs segmentation of an image for every haze color and estimates the airlight, the transmission, and the weight of dehaze in each segmentation area individually. Most of haze removal algorithms require a tone curve correction as post processing. However, it is very difficult to select an optimal tone curve correction for any image. To deal with this problem, the authors propose a novel algorithm that does not require any tone curve correction. The general haze removal algorithm treats only haze image. However, in the field of outdoor camera surveillance, it's desirable to realize the algorithm which can be applied to various weather conditions. The authors algorithm can detect snowfall at high speed and stably not only in bad weather but also in good weather.

• Record URL:
  https://doi.org/10.1109/ITSC.2014.6958181
• Availability:
  • Find a library where document is available. Order URL: http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6948869
• Supplemental Notes:
  • Abstract reprinted with permission of IEEE.
• Corporate Authors:

  Institute of Electrical and Electronics Engineers (IEEE)

  3 Park Avenue, 17th Floor
  New York, NY  United States  10016-5997
• Authors:
  • Kawarabuki, H
  • Onoguchi, K
• Conference:
  • 17th International IEEE Conference on Intelligent Transportation Systems (ITSC14)
  • Location: Qingdao , China
  • Date: 2014-10-8 to 2014-10-11
• Publication Date: 2014-10

Language

• English

Media Info

• Media Type: Web
• Pagination: pp 3058-3063
• Monograph Title: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC14)

Subject/Index Terms

• TRT Terms: Algorithms; Cameras; Detection and identification; Haze; Image processing; Snowfall; Weather conditions
• Subject Areas: Highways; Planning and Forecasting; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01562079
• Record Type: Publication
• Files: TRIS
• Created Date: Apr 28 2015 3:09PM