An Image Data Learning Method by Discriminating Multiple ROIs Data Patterns for Extracting Weather Information

Jiwan Lee, Sunghoon Jung, Kijin Kim, Minhwan Kim, Bonghee Hong

2017

Abstract

In order to generate weather information about rainfall and foggy visibility through analysis of CCTV images, the analysis on the changing patterns of time-series image data is a new approach to generating weather information from CCTV images. This paper demonstrates a method to generate optimum ROIs for extracting subtle weather image changes caused by fog and rainfall. It suggests the optimum ROI size and distance interval between ROIs through experiments. Finally, a clustering-based method for extracting weather information is proposed that has different data pattern difference between ROIs as a learning model, which is based on the suggested optimum ROI size and interval.

References

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Paper Citation


in Harvard Style

Lee J., Jung S., Kim K., Kim M. and Hong B. (2017). An Image Data Learning Method by Discriminating Multiple ROIs Data Patterns for Extracting Weather Information . In Proceedings of the 2nd International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS, ISBN 978-989-758-245-5, pages 438-443. DOI: 10.5220/0006380404380443


in Bibtex Style

@conference{iotbds17,
author={Jiwan Lee and Sunghoon Jung and Kijin Kim and Minhwan Kim and Bonghee Hong},
title={An Image Data Learning Method by Discriminating Multiple ROIs Data Patterns for Extracting Weather Information},
booktitle={Proceedings of the 2nd International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,},
year={2017},
pages={438-443},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006380404380443},
isbn={978-989-758-245-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,
TI - An Image Data Learning Method by Discriminating Multiple ROIs Data Patterns for Extracting Weather Information
SN - 978-989-758-245-5
AU - Lee J.
AU - Jung S.
AU - Kim K.
AU - Kim M.
AU - Hong B.
PY - 2017
SP - 438
EP - 443
DO - 10.5220/0006380404380443