CFP last date
20 January 2025
Reseach Article

Comparative Analysis of Lossless Text Compression Techniques

by Nathanael Jacob, Priyanka Somvanshi, Rupali Tornekar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 56 - Number 3
Year of Publication: 2012
Authors: Nathanael Jacob, Priyanka Somvanshi, Rupali Tornekar
10.5120/8871-2850

Nathanael Jacob, Priyanka Somvanshi, Rupali Tornekar . Comparative Analysis of Lossless Text Compression Techniques. International Journal of Computer Applications. 56, 3 ( October 2012), 17-21. DOI=10.5120/8871-2850

@article{ 10.5120/8871-2850,
author = { Nathanael Jacob, Priyanka Somvanshi, Rupali Tornekar },
title = { Comparative Analysis of Lossless Text Compression Techniques },
journal = { International Journal of Computer Applications },
issue_date = { October 2012 },
volume = { 56 },
number = { 3 },
month = { October },
year = { 2012 },
issn = { 0975-8887 },
pages = { 17-21 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume56/number3/8871-2850/ },
doi = { 10.5120/8871-2850 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:57:54.705100+05:30
%A Nathanael Jacob
%A Priyanka Somvanshi
%A Rupali Tornekar
%T Comparative Analysis of Lossless Text Compression Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 56
%N 3
%P 17-21
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Data compression is an effective means for saving storage space and channel bandwidth. There are two main types of compression lossy and lossless. This paper will deal with lossless compression techniques named Huffman, Arithmetic, LZ-78 and Golomb coding. The paper attempts to do comparative analysis in terms of their compression efficiency and speed. The test files used for this include English text files, Log files, Sorted word list and geometrically distributed data text file. The implementation results of these compression algorithms suggest the efficient algorithm to be used for a certain type of file to be compressed taking into consideration both the compression ratio and speed of operation. In terms of compression ratios, Golomb is best suited for very low frequency Text files, arithmetic for moderate and high frequency. Implementation is done using MATLAB software.

References
  1. Vikas Singla, Rakesh Singla and Sandeep Gupta, "Data compression modelling: Huffman and Arithmetic", International Journal of The Computer, the Internet and Management, Vol. 16 No. 3, Page(s):64- 68. Sept-Dec, 2008
  2. O. Srinivasa Rao, Prof. S. Pallam Setty, "Comparative Study of Arithmetic and Huffman Compression Techniques for Enhancing Security and Effective Bandwidth Utilization in the Context of ECC for Text", International Journal of Computer Applications, Vol. 29 No. 6, Page(s):44-60, September 2011.
  3. Ahmed S. Musa, Ayman Al-Dmour, Mansour I. Irshid, "An Efficient Text Compression Technique Based on Using Bitwise Lempel-Ziv Algorithm", Australian Journal of Basic and Applied Sciences, 4(12),ISSN 1991-8178, INSInet Publication, Page(s):6564-6569, 2010.
  4. Hsuan-Huei Shih, Shrikanth S. Narayanan and C. -C. Jay Kuo; "A Dictionary Approach To Repetitive Pattern Finding In Music", IEEE International Conference on Multimedia and Expo (ICME 2001) , Page(s): 397- 400.
  5. S. R. Kodituwakku, U. S. AMARASINGHE, "Comparison of lossless data compression algorithms for text data", Indian Journal of Computer Science and Engineering, ISSN : 0976-5166, Vol 1 No 4 416-425, 2010.
  6. Mamta Sharma, "Compression Using Huffman Coding", IJCSNS International Journal of Computer Science and Network Security, Vol. 10 No. 5, Page(s):133-141, May 2010.
  7. David A. Huffman, "A Method for the Construction of Minimum-Redundancy Codes", Proceedings of the IRE, Vol. 40, No. 9, Page(s): 1098-1101, September 1952.
  8. Jacob Ziv, Abraham Lempel, "Compression of Individual Sequences via Variable-Rate Coding", IEEE Transactions on Information Theory, Vol. 24, No. 5, Page(s):530-536, September 1978.
  9. Forrest Elliott and Manfred Huber, Learning Macros with an Enhanced LZ78 Algorithm, Technical Report CSE, The University of Texas at Arlington, 2005.
  10. David Salomon, Data Compression: The Complete Reference, Third edition, Pgs 185-188. Springer, 2004.
Index Terms

Computer Science
Information Sciences

Keywords

Huffman Arithmetic LZ-78 Golomb compression ratio