We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Improving the Efficiency of Block Matching Algorithms using Optimization Techniques

by Syed Ali Zia, Nasir Ahmad
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 175 - Number 14
Year of Publication: 2020
Authors: Syed Ali Zia, Nasir Ahmad
10.5120/ijca2020920622

Syed Ali Zia, Nasir Ahmad . Improving the Efficiency of Block Matching Algorithms using Optimization Techniques. International Journal of Computer Applications. 175, 14 ( Aug 2020), 22-25. DOI=10.5120/ijca2020920622

@article{ 10.5120/ijca2020920622,
author = { Syed Ali Zia, Nasir Ahmad },
title = { Improving the Efficiency of Block Matching Algorithms using Optimization Techniques },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2020 },
volume = { 175 },
number = { 14 },
month = { Aug },
year = { 2020 },
issn = { 0975-8887 },
pages = { 22-25 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume175/number14/31522-2020920622/ },
doi = { 10.5120/ijca2020920622 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:25:02.455467+05:30
%A Syed Ali Zia
%A Nasir Ahmad
%T Improving the Efficiency of Block Matching Algorithms using Optimization Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 175
%N 14
%P 22-25
%D 2020
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Block matching techniques are efficient methods among existing motion estimation methods according to literature. Block matching techniques mostly focuses on the factors like estimation accuracy and computational complexity. There are few methods among the existing search methods which can provide satisfactory result at a very low computational cost but none of these methods can effectively jump out of the local optimum when processing large motion sequences. The proposed search method mainly adopts threshold values for early termination of block-matching in order to remove unnecessary search and is evaluated and compared together in terms of signal to noise ratio and search point’s avoidance per macro block for different block size and search area. Experimental results showed that the proposed method has achieved significant improvement on both Estimation accuracy and computational complexity.

References
  1. Verma, V., & Mishra, R. (2013). Various Fast Block Matching Algorithm for Video Shot Boundary Detection. IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE), vol.4, no. 1, pp. 11-17.
  2. Chandra Sekhar, C.H., & Ratnam, J.V.K. (2012) “Comparison of Fast Block Matching Algorithms for Motion Estimation”, International Journal of Electronics and Computer Science Engineering (IJCSE), vol.1, no. 3, pp. 1609-1618.
  3. Immanuel, S., Pandian, A., & George, B.A. (2011) “A Study on Block Matching Algorithms for Motion Estimation”, International Journal on Computer Science and Engineering (IJCSE), vol. 3, no. 1, pp. 34-44.
  4. Stiller, C., & Konrad, J. (1999) “Estimating motion in image sequences”, IEEE Signal Processing Magazine, vol. 16, no. 4, pp. 70-91.
  5. Arvanitidou, M. G., Tok, M., Glantz, A., Krutz, A., & Sikora, T. (2013) “Motion-based object segmentation using hysteresis and bidirectional inter-frame change detection in sequences with moving camera”, Signal Processing: Image Communication, vol. 28, no. 10, pp. 1420-1434.
  6. Pradhan, C., & Adak, D. (2012). “Survey on block matching algorithms for motion estimation”, International Journal of Computer Applications, vol. 46, no. 16, pp. 6-10.
  7. Bouthemy, P. (2004). “2D motion description and contextual motion analysis: Issues and new models”, International Workshop on Spatial Coherence for Visual Motion Analysis, Springer, Berlin, Heidelberg. pp. 1-15.
  8. Rodriguez, A., Fernandez-Lozano, C., Dorado, J., & Rabuñal, J. R. (2014) “Two-Dimensional Gel Electrophoresis Image Registration Using Block-Matching Techniques and Deformation Models.” Analytical Biochemistry, 454.1, pp. 53–59.
  9. Ng, K. H., Po, L. M., Wong, K. M., Ting, C. W., & Cheung, K. W. (2009) “A search patterns switching algorithm for block motion estimation”, IEEE Transactions on Circuits and Systems for Video Technology, vol. 19, no. 5, pp. 753-759.
  10. Ng, K. H., Po, L. M., Wong, K. M., Ting, C. W., & Cheung, K. W. (2009) “Multiple block-size search algorithm for fast block motion estimation”, IEEE 7th International Conference on Information, Communications and Signal Processing (ICICS), pp. 1-4.
  11. Jagiwala, D. D., & Shah, M. S. (2012) “Analysis of block matching algorithms for motion estimation in H. 264 video CODEC”, Analysis, vol. 2, no. 6, pp. 1396-1401.
  12. Metkar, S., & Talbar, S. (2013) “Performance evaluation of block matching algorithms for video coding”, Motion Estimation Techniques for Digital Video Coding, Springer, India, pp. 13-31,
  13. Rodriguez, A., Rabuñal, J. R., Pérez, J. L., & Martínez‐Abella, F. (2012) “Optical analysis of strength tests based on block‐matching techniques”, Computer‐Aided Civil and Infrastructure Engineering, vol. 27, no. 8, pp. 573-593.
  14. Tourapis, A. M., Wu, F., & Li, S. (2005) “Direct mode coding for bipredictive slices in the H. 264 standard” IEEE Transactions on circuits and systems for video technology, vol. 15, no. 1, pp. 119-126.
  15. Freire, A., Seoane, J. A., Rodríguez, Á., Ruiz-Romero, C., López-Campos, G., & Dorado, J. (2010) “A Block-matching based technique for the analysis of 2D gel images”, MedInfo, pp. 1282-1286.
  16. Mishra, S. S., Pradhan, C., & Singh, A. (2014) “Comparative study of motion estimation techniques in video”, Int. J. Comput. Sci. Inf. Technol, vol. 5, no. 3, pp. 2982-2989.
  17. Cheng, S. C., & Hang, H. M. (1997) “A comparison of block-matching algorithms mapped to systolic-array implementation”, IEEE Transactions on Circuits and Systems for Video Technology, vol. 7, no. 5, pp. 741-757.
  18. Seferidis, V. E., & Ghanbari, M. (1993) “General approach to block-matching motion estimation”, Optical Engineering, vol. 32, no. 7, pp. 1464-1475.
  19. Nie, Y., & Ma, K. K. (2002) “Adaptive rood pattern search for fast block-matching motion estimation”, IEEE Transactions on Image processing, vol. 11, no.12, pp. 1442-1449.
  20. Manjunatha, D. V., & Sainarayanan, D. (2011) “Comparison and implementation of fast block matching motion estimation algorithms for video compression”, Int. J. Eng. Sci. Technol.(IJEST), vol. 3, no. 10, pp. 7608-7613.
  21. Rajamanickam, V., & Marikkannan, S. (2016) “Efficient Block-Based Motion Estimation Architecture Using Particle Swarm Optimization”, Int. Arab J. Inf. Technol., vol. 13, no.6A, pp. 732–739.
  22. Cai, J., & Pan, W. D. (2010) “Fast exhaustive-search motion estimation based on accelerated multilevel successive elimination algorithm with multiple passes”, IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 1190-1193.
  23. Korat, P. N., & Bhojani, D. R. (2014) “A new hybrid block-based motion estimation algorithm for video compression”, Int. J. Adv. Res. Electr., Electron. Instrum. Engg, pp. 9586–9596.
  24. Tok, M., Eiselein, V., & Sikora, T. (2015) “Motion modeling for motion vector coding in HEVC”, IEEE Picture Coding Symposium (PCS), pp. 154-158.
  25. Po, L. M., Ng, K. H., Cheung, K. W., Wong, K. M., Uddin, Y. M. S., & Ting, C. W. (2009) “Novel directional gradient descent searches for fast block motion estimation”, IEEE Transactions on Circuits and Systems for Video Technology, vol. 19, no. 8, pp. 1189-1195.
Index Terms

Computer Science
Information Sciences

Keywords

Motion Estimation Block matching fast search Block Termination Local Minima.

Powered by PhDFocusTM