TY - JOUR
T1 - Clustering learning model of CCTV image pattern for producing road hazard meteorological information
AU - Lee, Jiwan
AU - Hong, Bonghee
AU - Jung, Sunghoon
AU - Chang, Victor
N1 - Publisher Copyright:
© 2018 Elsevier B.V.
PY - 2018/9
Y1 - 2018/9
N2 - A method for real-time estimation of weather, especially the amount of rainfall, by analyzing CCTV images, is much cheaper than one using the existing expensive weather observation equipment. In this paper, we propose a method to find an estimation model function whose input is CCTV images and output is the amount of rainfall. Using CCTV images, we propose an algorithm for selecting the number and size of the region of interest optimized for rainfall estimation, generating a data pattern graph showing a clear distinction from the number of regions of interest, clustering the pattern data graphs, and estimating the amount of rainfall. Experiments using real CCTV images show that the estimation accuracy is greater than 80%.
AB - A method for real-time estimation of weather, especially the amount of rainfall, by analyzing CCTV images, is much cheaper than one using the existing expensive weather observation equipment. In this paper, we propose a method to find an estimation model function whose input is CCTV images and output is the amount of rainfall. Using CCTV images, we propose an algorithm for selecting the number and size of the region of interest optimized for rainfall estimation, generating a data pattern graph showing a clear distinction from the number of regions of interest, clustering the pattern data graphs, and estimating the amount of rainfall. Experiments using real CCTV images show that the estimation accuracy is greater than 80%.
UR - http://www.scopus.com/inward/record.url?scp=85046757272&partnerID=8YFLogxK
U2 - 10.1016/j.future.2018.03.022
DO - 10.1016/j.future.2018.03.022
M3 - Article
AN - SCOPUS:85046757272
SN - 0167-739X
VL - 86
SP - 1338
EP - 1350
JO - Future Generation Computer Systems
JF - Future Generation Computer Systems
ER -