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논문검색

An Approach on Automatic Tracking and Predicting of Satellite Cloud Clusters Based on Active Contour

초록

영어

The tracking and forecasting of satellite cloud images are very important in term of satellite cloud images used in weather forecast. An approach on automatic tracking of multi-target cloud cluster based on VFC Snake model is proposed on the basis of contour extraction and analysis of cloud cluster, this method can automatically acquire the new location of the target cloud cluster at each moment. A specialized detection algorithm is designed to correct the Snake's tracking results, and more accurate contour curves are obtained. For the forecasting of cloud images, the target cloud cluster’s displacement obtained in the tracking process is integrated into the cross-correlation matching to improve the matching accuracy of the cross-correlation method, and more accurate cloud motion vectors are obtained. The experimental results show that the tracking based on contour detection and analysis is fast and highly accurate, and the evolution process of cloud cluster can be directly obtained in a period of time (eg, split, merge, die and newborn), preferable results has also been made in forecasting.

목차

Abstract
 1. Introduction
 2. Automatic Tracking Method of Multi-target Cloud Cluster based onVFC Active Contour
  2.1. The Extraction of Initial Contour
  2.2. Cloud Cluster Split and Merge
  2.3. Cloud Cluster Die and Newborn
 3. Calculate the Wind Field
  3.1. Acquire the Whole Movement of Target Cloud Cluster
  3.2. Determine the Internal Movement of Cloud Cluster
 4. Short-term Forecast
 5. Conclusion
 References

저자정보

  • Mengmeng Cui Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science & Technology, School of Applied Meteorological Science, Nanjing University of Information Science & Technology
  • Yong Huang AnHui Institute of Meteorological Sciences
  • Shengjun Xue Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science & Technology
  • Jin Wang Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science & Technology

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