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Reseach Article

Measurement of Displacement and Velocity of a Moving Object from Real Time Video

by Pritam Das, Ranjit Ghoshal, Dipak Kumar Kole, Rabindranath Ghosh
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 49 - Number 13
Year of Publication: 2012
Authors: Pritam Das, Ranjit Ghoshal, Dipak Kumar Kole, Rabindranath Ghosh
10.5120/7685-0992

Pritam Das, Ranjit Ghoshal, Dipak Kumar Kole, Rabindranath Ghosh . Measurement of Displacement and Velocity of a Moving Object from Real Time Video. International Journal of Computer Applications. 49, 13 ( July 2012), 12-16. DOI=10.5120/7685-0992

@article{ 10.5120/7685-0992,
author = { Pritam Das, Ranjit Ghoshal, Dipak Kumar Kole, Rabindranath Ghosh },
title = { Measurement of Displacement and Velocity of a Moving Object from Real Time Video },
journal = { International Journal of Computer Applications },
issue_date = { July 2012 },
volume = { 49 },
number = { 13 },
month = { July },
year = { 2012 },
issn = { 0975-8887 },
pages = { 12-16 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume49/number13/7685-0992/ },
doi = { 10.5120/7685-0992 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:47:05.856999+05:30
%A Pritam Das
%A Ranjit Ghoshal
%A Dipak Kumar Kole
%A Rabindranath Ghosh
%T Measurement of Displacement and Velocity of a Moving Object from Real Time Video
%J International Journal of Computer Applications
%@ 0975-8887
%V 49
%N 13
%P 12-16
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This article focuses on an efficient algorithm for measuring object displacement and velocity from real time video. The proposed technique for object identification and tracking is based on background subtraction with optimized threshold binarization. Mapping techniques have been developed to relate image with real world. The algorithm is also capable of working with a bad lighting conditions using histogram equalization approach. Further, the real scenarios like presence of noise, shadow, and multiple moving object environments have been taken under consideration for developing the algorithm.

References
  1. Alper Yilmaz, Ohio State University, Omar Javed, ObjectVideo, Inc. , and Mubarak Shah, University of Central Florida, Object Tracking: A Survey, ACM Computing Surveys, Vol. 38, No. 4, Article 13, Publication date: December 2006.
  2. Duy-Nguyen Ta, Georgia Institute of Technology, Wei-Chao Chen, Natasha Gelfand and Kari Pulli, Nokia Research Center, Palo Alto, SURFTrac: Efficient Tracking and Continuous Object Recognition using Local Feature Descriptors, CVPR 2009:2937-2944.
  3. XuLiang, Image Binarization using Otsu Method, NLPR-PAL Group, CASIA Conference, pp 345-349, 2009.
  4. N. Otsu. A Threshold Selection Method from Gray-Level Histograms, IEEE Transactions on Systems, Man, and Cybernetics, vol. 9, no. 1, pp. 377-393, 1979.
  5. U. Bhattacharya, S. K. Parui and S. Mondal, Devanagari and Bangla Text Extraction from Natural Scene Images, 10th International Conference on Document Analysis and Recognition, 2009
  6. Graham Leedham, Chen Yan, Kalyan Takru, Joie Hadi Nata Tan and Li Mian, Comparison of Some Thresholding Algorithms for Text/Background Segmentation in Difficult Document Images, Proceedings of the Seventh International Conference on Document Analysis and Recognition (ICDAR 2003), 2003.
  7. Dipak Kumar Kole and Amiya Halder, Automatic Brain Tumor Detection and Isolation of Tumor Cells from MRI Images, International Journal of Computer Applications, Vol. 39, No. 16,pp. 26-30, February 2012.
  8. Damien Lefloch, Real-Time People Counting system using Video Camera, Department of Computer Science and Media Technology, Gjøvik University College, Norway, 2007.
  9. Johan Sommerfeld, Image processing and object tracking from single camera, KTH Electrical Engineering, Stockholm, Sweden 2006-12-13.
  10. M Gangadharappa, Pooja Goel and Rajiv Kapoor, Anomaly Detection in Surveillance Video using Color Modeling, International Journal of Computer Applications, Vol. 45, No. 14,pp. 1-6, May 2012.
  11. Abhi R Varma, Seema V Arote, Chetna Bharti and Kuldeep Singh, Accident Prevention Using Eye Blinking and Head Movement, IJCA Proceedings on Emerging Trends in Computer Science and Information Technology -2012, April 2012.
  12. Ahmad Sedkyadly, M B Abdelhalim and Amrbadr, Analyzing and Measuring Human Joints Movements using a Computer Vision System, International Journal of Computer Applications, Vol. 45, No. 20,pp. 21-29, May 2012.
  13. Amiya Halder, Soumajit Pramanik and Arindam Kar, Dynamic Image Segmentation using Fuzzy C- means based Genetic Algorithm, International Journal of Computer Applications, Vol. 28, No. 6,pp. 15-20, August 2011.
  14. Rafael C. Gonzalez and Richard E. Woods, Digital Image Processing, Prentice-Hall, Inc. , second edition, 2001.
Index Terms

Computer Science
Information Sciences

Keywords

Video Capture Histogram Equalization CLAHE Binarization Background Estimation Background Subtraction Mapping Camera Coverage Camera Span Displacement and Velocity Memory Management Time Complexity