Contact Us Search Paper

An Enhanced Coding Algorithm for Efficient Video Coding

V. R. Prakash*, Saran

Corresponding Author:

V. R. Prakash

Affiliation(s):

Electronics and Communication Engineering, St. Michael engineering college, Madurai, India
*Corresponding author: [email protected]

Abstract:

With the advancement in modern video processing technologies, the requirement of an efficient coding algorithm for compressing the video data in a huge surveillance system is necessary. The video data rate in a surveillance system plays a crucial role in determining the performance of the compression algorithm. In this paper, a novel compression algorithm for effectively compressing the video inputs from the surveillance systems is presented. The traditional methods fail to eliminate the redundancies in the video input, and can’t meet the current requirement standards in the modern technologies. This results in the increased storage requirement for input video and also makes it time-consuming in processing the video input in real time. In order to overcome the above issues, the proposed algorithm made sufficient modification in the traditional run length coding algorithm by encoding the frames and removing the redundancies using the texture information similarity in the surveillance video, thereby achieved a better compression rate of 50% for a huge dataset of surveillance videos when compared to existing methodologies.

Keywords:

Run Length Coding; Global Redundancies; Compression Ratio; Texture Feature; Similarity Measurement

Downloads: 664 Views: 7762
Cite This Paper:

V. R. Prakash, Saran (2019). An Enhanced Coding Algorithm for Efficient Video Coding. Journal of the Institute of Electronics and Computer, 1, 28-38. https://doi.org/10.33969/JIEC.2019.11004.

References:

[1] Jing Xiao, Liang Liao, Jinhui Hu, Yu Chen, Ruimin Hu. 2015. Exploiting global redundancy in big surveillance video data for efficient coding. Springer Science Business Media New York, 18: pp. 531-540.
[2] Amritha, K. M. Nithin, S S. 2015. Adaptive Encoding & Decoding of Compressed Video Using SPIHT Algorithm. International Journal of Advanced Research in Computer Engineering & Technology (IJARCET), 4(5): pp. 2409-2412.
[3] Kamisli, F. 2015. Block-Based Spatial Prediction and Transforms Based on 2D Markov Processes for Image and Video Compression. IEEE Transactions on Image Processing, 24(4): pp.1247-1260.
[4] Ma, M. Hu, R. Chen, S. Xiao, J. Wang, Z. Qu, S. 2015. Global Object Representation of Scene Surveillance Video Based on Model and Feature Parameters. Advances in Multimedia Information Processing - PCM 2015, 9314: pp 223-232.
[5] Yin-Tsung, H. Ming-Wei, L. Cheng-Chen, L. 2015. A Low-Complexity Embedded Compression Codec Design With Rate Control for High-Definition Video. IEEE Transactions on Circuits and Systems for Video Technology, 25(4): pp.674-687.
[6] Zhang, Y. Agrafiotis, D. Bull, D. R. 2013. High Dynamic Range image & video compression a review. 2013 18th International Conference on Digital Signal Processing (DSP), Fira, pp. 1-7.
[7] Liu, F. Koenig, H. 2014. Puzzle-an efficient, compression independent video encryption algorithm.  Multimedia Tools and Applications, 73(2): pp. 715-735.
[8] Xu, M. 2014. Compressibility constrained sparse representation with learnt dictionary for low bit-rate image compression. IEEE Trans. Circuits Syst. Video Technol,. 24(10): pp.1743–1757.
[9] Zhang, X. 2014. Background-modeling-based adaptive prediction for surveillance video coding. IEEE Trans. Image Process,. 23(2): pp. 769–784.
[10] AntoBennet, M. Nithyadevi, R. Jacob Reglend, I.  Nagarajan, C. 2013. Performance and Analysis of Video Compression Using Block Based Singular Value Decomposition Algorithm. International Journal of Modern Engineering Research (IJMER), 3(3): pp-1482-1486.
[11] Chongyu Chen, JianfeiCai, Weisi Lin, Guangming Shi. 2012. Surveillance Video Coding via Low-Rank and Sparse Decomposition.  Proceedings of the 20th ACM international conference on Multimedia (MM '1), pp. 713-716.
[12] Prakash, V.R. Nagarajan, S. 2019. Intelligent systems for redundancy removal with proficient run-length coding and statistical analysis using regression. International Journal of Intelligent Systems Technologies and Applications, 18(1): pp. 101-114.
[13] Prakash, V.R. Nagarajan, S. 2019. Utilizing global redundancy in BSVD using RR- ERLC for efficient video coding.  International Journal of Control Theory and Applications, 9(34): pp. 833-841.