On the application of wavelet transform and Huffman algorithm to Yorùbá language syntax text files compression

Most algorithms of data compression were developed with English language as target text syntax. However, this paper approaches the problem of Yor?b? text files compression via the use of Discrete Wavelet Transform (DWT) and Huffman algorithm. Text files in Yor?b? language syntax are first converted...

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Bibliographic Details
Published in:Serbian journal of electrical engineering Vol. 19; no. 3; pp. 351 - 368
Main Authors: Amusa, Kamoli, Adewusi, Adeoluwawale, Erinosho, Tolulope, Salawu, Sule, Odufejo, David
Format: Journal Article
Language:English
Published: Faculty of Technical Sciences in Cacak 2022
Subjects:
compression
huffman coding
text file
wavelet transform
yorùbá language syntax
ISSN:1451-4869, 2217-7183
Online Access:Get full text
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Summary:Most algorithms of data compression were developed with English language as target text syntax. However, this paper approaches the problem of Yor?b? text files compression via the use of Discrete Wavelet Transform (DWT) and Huffman algorithm. Text files in Yor?b? language syntax are first converted into signal format that are then decomposed using DWT. The decomposed ASCII code representation of the text files are subsequently encoded using Huffman algorithm. Twenty different variants of DWTs taken from four families of wavelet filters (Haar, Daubechies, Symlets and bi-orthogonal) are considered to select the optimal DWT for Yor?b? text files compression. Furthermore, experiments are carried out in the proposed compression scheme with six different Yor?b? text files extracted from the open sources as input data sets. It is found that out of the twenty variants of DWT investigated, sym6 gives the best output for effective Yor?b? text files compression, due to its relatively high compression ratio, high compression factor and lowest compression error. Thus, sym6 as a wavelet transform is suitable for lossy text compression algorithm meant for Yor?b? language syntax text files.
ISSN:1451-4869
2217-7183
DOI:10.2298/SJEE2203351A