Open Access   Article Go Back

A Review on Frame Indexing and Labeling in Dynamic Rainy Video Scenes with Rain Pixel Recovery

Punam P. Kansare1 , Ashwini Meshram2

Section:Review Paper, Product Type: Journal Paper
Volume-2 , Issue-12 , Page no. 98-100, Dec-2014

Online published on Dec 31, 2014

Copyright © Punam P. Kansare , Ashwini Meshram . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: Punam P. Kansare , Ashwini Meshram, “A Review on Frame Indexing and Labeling in Dynamic Rainy Video Scenes with Rain Pixel Recovery,” International Journal of Computer Sciences and Engineering, Vol.2, Issue.12, pp.98-100, 2014.

MLA Style Citation: Punam P. Kansare , Ashwini Meshram "A Review on Frame Indexing and Labeling in Dynamic Rainy Video Scenes with Rain Pixel Recovery." International Journal of Computer Sciences and Engineering 2.12 (2014): 98-100.

APA Style Citation: Punam P. Kansare , Ashwini Meshram, (2014). A Review on Frame Indexing and Labeling in Dynamic Rainy Video Scenes with Rain Pixel Recovery. International Journal of Computer Sciences and Engineering, 2(12), 98-100.

BibTex Style Citation:
@article{Kansare_2014,
author = {Punam P. Kansare , Ashwini Meshram},
title = {A Review on Frame Indexing and Labeling in Dynamic Rainy Video Scenes with Rain Pixel Recovery},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {12 2014},
volume = {2},
Issue = {12},
month = {12},
year = {2014},
issn = {2347-2693},
pages = {98-100},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=342},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=342
TI - A Review on Frame Indexing and Labeling in Dynamic Rainy Video Scenes with Rain Pixel Recovery
T2 - International Journal of Computer Sciences and Engineering
AU - Punam P. Kansare , Ashwini Meshram
PY - 2014
DA - 2014/12/31
PB - IJCSE, Indore, INDIA
SP - 98-100
IS - 12
VL - 2
SN - 2347-2693
ER -

VIEWS PDF XML
3485 3270 downloads 3468 downloads
  
  
           

Abstract

Rain act as a noise that affect videos and images. Mostly, noises are observed due to weather conditions that will affect audio correspondence, object recognition, motion segmentation, and object tracking. While editing movie or any security surveillance if any problem is found due to rain constraints the object cannot be tracked well. Rain drops are spatially distributed which falls at very high velocities. Hence, it leads to produce sharp intensity variations in an image where each drop refracts and reflects the environment. Such group of falling rain drops generates a complex time varying signal in both images as well as in videos. Random rain pixel detection and noise filtrations lead to achieve the high performance in dynamic videos having various vision-based applications. So, by extracting the key frames from the large size video we can compress it to smaller one which helps to retrieve dynamic frame through indexing and labeling. After the key frame selection rain pixel recovery algorithm will provide the compressed video with the rain pixel recovery from highly dynamic scenes.

Key-Words / Index Term

Rain Detection, Properties, Background Subtraction, Spatial-Temporal, Rain Removal, Static Weather Condition, Dynamic Weather Condition, Frame Indexing and Labeling

References

[1]Jie Chen and Lap-Pui Chau, ‘‘A Rain Pixel Recovery Algorithm for Videos with Highly Dynamic Scenes”, IEEE Image Processing, vol. 23, no. 3, March2014.
[2] Kshitiz Garg and Shree K. Nayar, “Vision and Rain”, International Journal of Computer Vision 75(1), 3–27, February 2007
[3] K. Garg and S.K. Nayar, "Detection and removal of rain from videos," in IEEE Conf. Computer Vision and Pattern Recognition, vol. 1, pp. 528-535, 2004.
[4] X. Zhang, H. Li, Y. Qi, W.K. Leow and T.K. Ng, "Rain Removal in Video by Combining Temporal and Chromatic Properties," in IEEE Int. Conf. Multimedia and Expo, pp. 461-464, 2006.
[5] Peter C. Barnum ,Srinivasa Narasimhan ,Takeo Kanade “Analysis of Rain and Snow in Frequency Space”, Springer International Journal of Computer Vision 86,256-274, 2010.
[6] Ming Zhou, Zhichao Zhu, Rong, Deng, Shuai Fang,Rain, “Detection and Removal of Sequential Images”, IEEE Chinese Control and Decision Conference (CCDC), pp. 615-618, 2011.
[7] Abhishek Kumar Tripathi, Sudipta Mukhopadhyay, “A Probabilistic Approach for Detection and Removal of Rain from Videos”, IETE Journal of Research, vol. 57, pp. 82-91, 2011.
[8] Stuart, A., and Ord, J.K., Kendall’s Advanced Theory of Statistics, 5th edition, 1987, vol 1, section 10.15.
[9]http://mathworld.wolfram.com/PearsonsSkewnessCoefficients.html
[10] Jeremie Bossu, Nicolas Hautiere, Jean-Philippe Tarel, “Rain or Snow Detection in Image Sequences Through Use of a Histogram of Orientation of Streaks”, Springer International Journal of Computer Vision, January 2011.