Estimation of Rain Drop Size using Image Processing

Shraddha Dilip Shetye, Yadavrao Tasgaonkar Institute of Engineering & Technology; Pandharinath A Ghonge ,Yadavrao Tasgaonkar Institute of Engineering & Technology

DSD, Image Segmentation, rain guage, disdrometer etc

The drop size distribution (DSD) has awesome variety in various sorts of precipitation condition. The DSD can likewise decide diverse snapshot of rainfall. Image processing tool can help to analyses rain in the space. An enhanced mean filter is executed for de-noising of exceptionally tainted and edge protection of a picture. Picture division regularly used to recognize the frontal area from background. Biclustering calculations in view of vertical and horizontal arrays mean value an incentive to choose the limit at the nearby mean. Elective calculation is tried with same information; separation estimation is utilized to converge to pixels. It specifically approaches the feasibility of assessing the decency of each match and naturally gathering the nearer combine ought to be nearest in the feeling of mean separation. All means are rehashed until accomplishing two clusters. Results obtained from automatic thresholding of picture are demonstrating legitimacy of the method. Morphological operators are most helpful for depiction of the state of the objects.
    [1] Pei-Eng Ng and Kai-Kuang Ma, “A Switching Median Filter with BDND for Extremely Corrupted Images”, IEEE Trans Image Processing, Vol. 15, No. 6, PP. 1506-1516, June 2006 [2] Jafar Ramadhan Mohammed, “An Improved Median Filter Based on Efficient Noise Detection for High Quality Image Restoration,”,IEEE Int. Conf ,PP. 327 – 331, . May 2008 [3] Xiaoyin Xu, Eric L. Miller, Dong bin Chen and Mansoor Sarhadi, “Adaptive Two-Pass Rank Order Filter to Remove Impulse Noise in Highly Corrupted Images”, IEEE Trans Image Processing,Vol.13,No.2, PP.238-247, February 2004. [4] Umbaugh Scot E, Computer Vision and Image Processing, Prentice Hall, NJ, 1998, ISBN 0-13-264599-8 [5] R.C.Gonzales, R.E.Woods, Digital Image Processing. 2-nd Edition, Prentice Hall, 2002. [6] S.-M. Lee, A. L. Abbott, N. A. Clark, and P. A. Araman, A shape representation for planar curves by shape signature harmonic embedding, in Proc. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2006. [7] S. Tabbone, L. Wendling, and J.-P. Salmon, A new shape descriptor dened on the radon transform, Computer Vision and Image Understanding, vol. 102(1), pp. 42_51, 2006. [8] G. Borgefors, _Distance transformations in digital images,_ in Computer Vision, Graphics, and Image Processing,June 1986, pp. 344_371. [9] G. S. di Baja and E. Thiel, Skeletonization algorithm running on path-based distance maps, Image Vision Computer, vol. 14, pp. 47_57, 1996. [10] A. Dubinskiy and S. C. Zhu, A multi-scale generative model for animate shapes and parts, in Proc. Ninth IEEE International Conference on Computer Vision (ICCV), 2003.
Paper ID: GRDJEV02I050053
Published in: Volume : 2, Issue : 5
Publication Date: 2017-05-01
Page(s): 47 - 52