Extraction and Enhancement of Moving Objects in a Video

  • Sumati ManchandaEmail author
  • Shanu Sharma
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 553)


Detection of objects for relocation in a video is a vital as well as initial step for many computer vision-based applications like moving object extraction, video surveillance, pattern classification, etc. The traditional methods used for detection of foreground objects include background subtraction, optical flow and frame differencing techniques. These methods are found to be advantageous only if the extraction of the moving object is precise and clearly visible that it is, the object must be of good quality. This paper emphasizes on the detection as well as the enhancement of the foreground objects. The proposed method uses the amalgam of two traditional techniques background subtraction and motion vector-based optical flow method along with morphological operators to extricate the nonstationary objects from the videos followed by the enhancement of the extracted object to be of better quality in terms of visibility. The proposed algorithm is executed over the videos having frame dimension of 640 × 360 along with the frame rate of 30 frames/second using MATLAB R2013.


Object extraction Enhancement Optical flow Background subtraction Median filter Morphological operators 


  1. 1.
    Soharab Hossain Shaikh, Khalid Saeed and Nabendu Chaki, “Moving Object Detection Using Background Subtraction” Springer Briefs in Computer Science, Springer International Publishing, 2014.Google Scholar
  2. 2.
    Kaur, R. and Singh,S. “Background modelling, detection and tracking of human in video surveillance system”, Innovative Applications of Computational Intelligence on Power, Energy and Controls with their impact on Humanity, pp. 54–58, 2014.Google Scholar
  3. 3.
    Karamiani, Aziz, and Nacer Farajzadeh.”Optimal feature points for tracking multiple moving objects in active camera model”, Multimedia Tools and Applications, 2015.Google Scholar
  4. 4.
    Sighla Nishu, “Motion Detection Based on Frame Difference Method”, International Journal of Information & Computation Technology, Vol 4 No. 15, pp. 1559–1565, 2014.Google Scholar
  5. 5.
    Rakibe Rupali S. and Patil Bharti D, “Background Subtraction Algorithm Based Human Motion Detection”, International Journal of Scientific and Research Publication, Vol 3, No. 5, May 2013.Google Scholar
  6. 6.
    Wu-Chih, Chao-Ho Chen, Tsong-Yi Chen, Deng-Yuan Huang and ZongChe Wu, “Moving object detection and tracking from video captured by moving camera”, Journal of Visual Communication and Image Representation, Vol 30 Pages 164–180, July 2015.Google Scholar
  7. 7.
    K. Kalirajan and M. Sudha, “Moving Object Detection for Video Surveillance” Hindawi Publishing Corporation Scientific World Journal Volume 2015, Article ID 907469. 2015.Google Scholar
  8. 8.
    P.N. Pathirana, A.E.K. Lim, J. Carminati, M. Premaratne, “Simultaneous estimation of optical flow and object state, A modified approach to optical flow calculation”. In Proceeding of IEEE International Conference on Networking, Sensing and Control, pp. 634–638, 2007.Google Scholar
  9. 9.
    Manvi, R.S. Chauhan and M. Singh, “Image contrast enhancement using histogram equalization”, International Journal of Computing & Business Research, I-Society12, no. 33, 2012.Google Scholar
  10. 10.
    Sharma Urvashi, Sharma Tripti And Jain Trisha, “Efficient Object Detection With Its Enhancement”, International Conference On Computing, Communication And Automation (ICCCA2015).Google Scholar
  11. 11.
    Khare, Manish, Rajneesh Kumar Srivastava, and Ashish Khare. “Object tracking using combination of daubechies complex wavelet transform and Zernike moment”, Multimedia Tools and Applications, 2015.Google Scholar
  12. 12.
    Arwa Darwish Alzughaibi, Hanadi Ahmed Hakami and Zenon Chacxzko, “Review of Human Motion Detection Based On Background Subtraction Techniques”, International Journal of Computer Allocations Volume 122, No 13, July 2015.Google Scholar
  13. 13.
    Asim R. Aldhaheri And Eran A. Edirisinghe, “Detection And Classification Of A Moving Object In A Video Stream”, Proc Of The International Conference On Advances In Computing And Information Technology-ACIT 2014.Google Scholar
  14. 14.
    Hu, W., Tan, T., Wang, L., Maybank, S., 2004. A survey on visual surveillance of object motion and behaviors. IEEE Trans. On System Man Cybernetics August 2012.Google Scholar
  15. 15.
    Abhishek Kumar Chauhan, Prashant Krishan, “Moving Object Tracking Using Gaussian Mixture Model And Optical Flow”, proc Of International Journal Of Advanced Research And Software Engineering, April 2013.Google Scholar
  16. 16.
    Dongxiang Zhou; Hong Zhang, “Modified GMM background modeling and optical flow for detection of moving objects”, International Conference on in Systems, Man and Cybernetics, vol. 3, pp. 2224–2229, Oct. 2005.Google Scholar
  17. 17.
    Dongxiang Zhou; Hong Zhang, “Modified GMM background modeling and optical flow for detection of moving objects”, International Conference on in Systems, Man and Cybernetics, vol.3, pp. 2224–2229, Oct. 2005.Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  1. 1.Department of Computer Science & EngineeringASET Amity UniversityNoidaIndia

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