CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
Reseach Article

Implementation of Running Average Background Subtraction Algorithm in FPGA for Image Processing Applications

by S. Susrutha Babu, S. Suparshya Babu, Habibulla Khan, M. Kalpana Chowdary
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 73 - Number 21
Year of Publication: 2013
Authors: S. Susrutha Babu, S. Suparshya Babu, Habibulla Khan, M. Kalpana Chowdary
10.5120/13022-0259

S. Susrutha Babu, S. Suparshya Babu, Habibulla Khan, M. Kalpana Chowdary . Implementation of Running Average Background Subtraction Algorithm in FPGA for Image Processing Applications. International Journal of Computer Applications. 73, 21 ( July 2013), 41-46. DOI=10.5120/13022-0259

@article{ 10.5120/13022-0259,
author = { S. Susrutha Babu, S. Suparshya Babu, Habibulla Khan, M. Kalpana Chowdary },
title = { Implementation of Running Average Background Subtraction Algorithm in FPGA for Image Processing Applications },
journal = { International Journal of Computer Applications },
issue_date = { July 2013 },
volume = { 73 },
number = { 21 },
month = { July },
year = { 2013 },
issn = { 0975-8887 },
pages = { 41-46 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume73/number21/13022-0259/ },
doi = { 10.5120/13022-0259 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:40:47.155597+05:30
%A S. Susrutha Babu
%A S. Suparshya Babu
%A Habibulla Khan
%A M. Kalpana Chowdary
%T Implementation of Running Average Background Subtraction Algorithm in FPGA for Image Processing Applications
%J International Journal of Computer Applications
%@ 0975-8887
%V 73
%N 21
%P 41-46
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper a new background subtraction algorithm was developed to detect moving objects from a stable system in which visual surveillance plays a major role. Initially it was implemented in MATLAB. Among all existing algorithms running average algorithm was choosen because of low computational complexity which is the major parameter of time in VLSI. The concept of the background subtraction is to subtract the current image with respect to the reference image and compare it with to the certain threshold values. We propose a new real time background subtraction algorithm which was implemented with verilog hdl in order to detect moving objects accurately. Our method involves three important modules background modelling; adaptive threshold estimation and finally fore ground extraction. Compared to all existing algorithms our method having low power consumption and low resource utilization. Here we have written the core processor Microblaze is designed in VHDL (VHSIC hardware description language), implemented using XILINX ISE 8. 1 Design suite the algorithm is written in system C Language and tested in SPARTAN-3 FPGA kit by interfacing a test circuit with the PC using the RS232 cable. Area and the speed of the algorithm are also evaluated.

References
  1. S. Herrero and J. Besc`os. Background subtraction techniques: systematic evaluation and comparative analysis. International conferenve on Advanced Concepts for Intelligent Vision Systems, pages 33–42, 2009.
  2. A Elgammal, D. Harwood, and L. Davis. Non-parametric model for background subtraction. European Conference on Computer Vision, pages 751–767, 2000.
  3. Du-Ming Tsai and Shia-Chih Lai, Independent Component Analysis-Based Background Subtraction for Indoor Surveillance, IEEE Trans. on Image Processing, 2009, 18(1), 158-167.
  4. Francis R. B. , and Michael I. J. , Kernel Independent Component Analysis, Journal of Machine Learning Research, 2002, 3,1-48.
  5. Susrutha Babu Sukhavasi, Suparshya Babu Sukhavasi, " Design of Modules to Implement a Structure by Discrete Reckoning Codes for Embedding Into Video Coding Testing Applications (IJMER), Vol. 2, Issue. 4, July-Aug 2012, pp-2867-2875 ISSN: 2249-6645.
  6. N. Lu, J. H. Wang, Q. H. Wu and L. Yang, "Motion detection based on accumulative optical flow and double background filtering," Proceedings of World Congress on Engineering, London, UK, 2-4 July, 2007, pp. 602-607.
  7. Object Tracking and Detecting Based on Adaptive Background Subtraction by Ruolin Zhang, Jian Ding in 2012 International Workshop on Information and Electronics Engineering (IWIEE).
  8. Background subtraction techniques: a review 2004 IEEE International Conference on Systems, Man and Cybernetics.
  9. Comparative Study of Background Subtraction Algorithms by Y. Benezeth P. -M. Jodoin B. Emile H. Laurent C. Rosenberge.
  10. Chen Trista P, Hanssecker Horst, Bovyrin Alexander, Belenov Roman, Rodyushkin Konstantin, Kuranov Alexander, "Computer Vision Workload Analysis : Case Study of Video Surveillance Systems," Intel Technology Journal , vol. 9, no. 2, pp. 109-118, May 2005.
  11. M. Bramberger, J. Brunner, and B. Rinner, "Real Time Video Analysis on an Embedded Smart Camera for Traffic Surveillance," in Proc. IEEE 10th Computer Society Conference on Real-Time and Embeded Technology and Applications, Symposium, May 2004, pp. 174-181.
Index Terms

Computer Science
Information Sciences

Keywords

Background Subtraction Micro blaze Object Detection UART VHDL