A Dynamic Image Compression using Improved LZW Encoding Algorithm

Authors

  • M. Sangeetha  M.E Research Scholar, Department of Computer Science and Engineering, Kumaraguru College of technology, Coimbatore, India
  • P. Betty  M.E Research Scholar, Department of Computer Science and Engineering, Kumaraguru College of technology, Coimbatore, India

Keywords:

RLE, LZW, JPEG, Compression, Delta Encoding

Abstract

Lossless image compression techniques seek the smallest possible image storage size for a specific level of image quality; in addition, dictionary-based encoding methods were initially implemented to reduce the one-dimensional correlation in text. The objective is to present a comparative measures of present techniques of image processing in accounts using compression techniques that are in use in Bio-metric images. Number of test has been performed to evaluate the presentation of projecting compression technique on the bio-metric data the performance reveals that LZW Compression algorithm having better accuracy of other predictive methods like Run-Length Encoding, Huffman Encoding, Delta Encoding, JPEG (Transform Compression) and MPEG algorithms are not performing well.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2017-02-28

Issue

Volume 2, Issue 1, January-February-2017

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
M. Sangeetha, P. Betty, " A Dynamic Image Compression using Improved LZW Encoding Algorithm, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 1, pp.264-270, January-February-2017.