A Dynamic Image Compression using Improved LZW Encoding Algorithm

Authors(2) :-M. Sangeetha, P. Betty

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.

Authors and Affiliations

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

RLE, LZW, JPEG, Compression, Delta Encoding

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Publication Details

Published in : Volume 2 | Issue 1 | January-February 2017
Date of Publication : 2017-02-28
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 264-270
Manuscript Number : CSEIT172156
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

M. Sangeetha, P. Betty, "A Dynamic Image Compression using Improved LZW Encoding Algorithm", International 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.
Journal URL : http://ijsrcseit.com/CSEIT172156

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