An efficient raindrop parameter estimation using image processing Online publication date: Mon, 19-Nov-2018
by Pandharinath Appasaheb Ghonge; Kushal R. Tuckley
International Journal of Reasoning-based Intelligent Systems (IJRIS), Vol. 10, No. 3/4, 2018
Abstract: Nowadays, image processing algorithms play a key role in the rain drop distribution estimation. This paper deals with number of drops and drop size distribution and its volume in particular time. We are using the raindrop image to calculate the amount of rainfall in a particular time. The proposed image processing based rain drop parameter estimation (IPRDPE) by using double-density dual-tree DWT (DDDT DWT) and thresholding based segmentation. By using effective image fusion technique, rain drop images from different angles are fused and using segmentation and morphological operations raindrop parameters estimated. To get better fused output max-based effective image fusion rules are used. The system using advanced image fusion technique and estimation for rain drop parameter, produce more accuracy and error free system compared to the existing techniques and also achieved better accuracy with respect to the real-time measurement.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Reasoning-based Intelligent Systems (IJRIS):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook