A Review on Tracking and Detecting Fish from Videos

Authors(2) :-Harmoninder Singh Brar, Er.Mandeep Kaur

Non-extractive fish abundance estimation with the aid of visual analysis has drawn increasing attention. Unstable illumination, ubiquitous noise and low frame rate video capturing in the underwater environment, however, make conventional tracking methods unreliable. In this paper, we present a multiple fish tracking system for low-contrast and low-frame-rate stereo videos with the use of a trawl-based underwater camera system. An automatic fish segmentation algorithm overcomes the low-contrast issues by adopting a histogram back projection approach on double local-threshold images to ensure an accurate segmentation on the fish shape boundaries. The problem of non-uniform illumination over the video frame by focusing only on the vicinity of each target. The Slowly moving objects detection are present in the scene such problems. A New algorithm for detection and tracking will be implemented in order to investigate improved efficiency. Furthermore, the algorithms developed to perform the video analysis, (such as pre-processing, detection, tracking and counting) could be integrated into a more generic architecture so that the best algorithm for each step will be selected.

Authors and Affiliations

Harmoninder Singh Brar
Guru Kashi University, Talwandi Sabo, Punjab, India
Er.Mandeep Kaur
Guru Kashi University, Talwandi Sabo, Punjab, India

Fish, Object, LFR, LED, Gaussian Model etc.

  1. Meng-CheChuang, Jenq-Neng wang, Kresimir Williams, Richard Towler “Tracking Live Fish from Low-Contrast and Low-Frame-Rate Stereo Videos” IEEE Trans. on Circuits and Systems for Video Technology, vol. 25, no. 1, pp.167-179, Jan. 2015
  2. Yun-Heh Chen-Burger , Gayathri Nadarajan, Robert B. Fisher “Detecting ,Tracking And Counting Fish In Low Quality Unconstrained Underwater Videos” Department of Informatics and Telecommunication Engineering, University of Catania, Catania, Italy,2015
  3. Srividya M. S., Hemavathy R., Shobha G. “Underwater Video Processing For Detecting And Tracking Moving Object” International Journal Of Engineering And Computer Science ISSN: 2319-7242 Volume 3 Issue 5, May 2014.
  4. M. S. Srividya, Shobha G. “A Survey on: Underwater Video Processing for Detecting and Tracking Moving Objects” International Journal of Soft Computing and Engineering (IJSCE) ISSN: 2231-2307, Volume-4, Issue-1, March 2014.
  5. E. Chandra and K. Kanagalakshmi, “Noise Suppression Scheme using Median Filter in Gray and Binary Images.” Int. J. Computer Applications 26, 2011.
  6. A. Azim and O. Aycard, "Multiple pedestrian tracking using Viterbi data association," Proc. of Intelligent Vehicles Symp. (IV), 2010 IEEE, pp.706-711, Jun. 2010.
  7. M.-C. Chuang, J.-N. Hwang, K. Williams and R. Towler, “Automatic fish segmentation via double local thresholding for trawl-based underwater camera systems,” Proc. of Image Processing, IEEE Int. Conf. on (ICIP ‘11), pp.3145-3148, Sep. 2011.
  8. Saman Poursoltan, Russell Brinkworth, Matthew Sorell “Biologically-inspired Video Enhancement Method For Robust Shape Recognition,” University of Adelaide, Australia, IEEE, 2013.
  9. Prabhakar C J & Praveen Kumar P U. “Feature Tracking of Objects in Underwater Video Sequences.”, Kuvempu University, India, ACEEE 2012.

Publication Details

Published in : Volume 2 | Issue 3 | May-June 2016
Date of Publication : 2016-06-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 352-356
Manuscript Number : IJSRSET1623106
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Harmoninder Singh Brar, Er.Mandeep Kaur, " A Review on Tracking and Detecting Fish from Videos, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 3, pp.352-356, May-June-2016.
Journal URL : http://ijsrset.com/IJSRSET1623106

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