A threshold-based thinning algorithm for a visual, automated snow-cover measurement system
| Autor: | Ik-Sang Shin, Soon-Geul Lee, Jong-Hyeong Kim |
|---|---|
| Rok vydání: | 2010 |
| Předmět: |
Computer science
business.industry Distortion (optics) System of measurement ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Process (computing) Snow Computer Science Applications Control and Systems Engineering Position (vector) Transfer (computing) Computer vision Artificial intelligence Scale (map) business Reliability (statistics) |
| Zdroj: | International Journal of Control, Automation and Systems. 8:99-106 |
| ISSN: | 2005-4092 1598-6446 |
| DOI: | 10.1007/s12555-010-0113-z |
| Popis: | An automated snow-cover measuring system is developed to measure the amount of snowfall by analyzing the visual image of a reference pole under an unstructured outdoor environment. The system consists of a reference pole, a CCD camera (including an infra-red module), and a PC which transfers the processed information to remote users via the Internet. The snow depth is estimated based on the lowest uncovered position of the pole with the captured image. After correcting the image distortion through an expansive coefficient curve, the corrected image is compared to a virtual measuring scale (VMS) for the accurate measurement. To enhance the visual measurement process, the captured images are pre-processed and the camera is calibrated for the natural outside light condition of the varied weather. The snow-cover measuring (SCM) algorithm is used to detect the height of the piled snow. This measuring system can also continuously transfer the raw images, as well as the estimated snow depth to remote clients through the Internet. The experimental results show that the system improves the reliability and accuracy of the measurement, and that it is convenient to use. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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