A Fast Image Compression Web Service Using a REST API
Abstract
A Fast Image Compression Web Service Using a REST API.
Â
Fidelis Odinma, Chete and Alexander Omorokunwa
Department of Computer Science, University of Benin, Benin City, Nigeria
Â
Â
Abstract – Images constitute a very important kind of data, and it forms an integral part of digital communication and other computer image processing applications. Due to their information-rich nature, images tend to require relatively large memory space to store them; and a lot of bandwidth to transmit them through a network. Compression makes it possible to reduce their file sizes while retaining a sufficient amount of quality that should still be pleasant to the human visual system. This compression can either utilize lossy or lossless compression techniques or methods. A novel web-based compression system was presented in this project, which uses a smart lossy compression algorithm served through a REST API. The system proved efficient from the results obtained from testing with random large-size image files. And acceptable compression ratio, compression time and space-saving percentages were derived in all the test cases.
Keywords - Web service, Image compression, lossy, lossless, REST API.
Full Text:
PDFReferences
References
S. Jain , A Mittal, and S Roy (2011). Model-based image compression framework for CT and MRI images. International Journal of Medical Engineering and Informatics, 3(1).
I. Mohammad and A. Zeekry (2015).Implementing Lossy Compression Technique for Video Codecs. International Journal of Computer Applications, 13(17), 44-51.
K Arora and M. Shukla, (2014). A Comprehensive Review of Image Compression Techniques. International Journal of Computer Science and Information Technologies, 5 (2), 1169-1172.
L.K. Tan (2006). Image File Formats. Biomedical Imaging and Intervention Journal, 2(1).
S. Thakur and S. Rai, (2018). A Study Image Compression Techniques for the Number of Applications. International Journal of Research and Innovation in Applied Science, 3(4).
R Goyal and J. Jaura, (2014) A Review of Various Image Compression Techniques. International Journal of Advanced Research in Computer Science and Software Engineering, 4(7).
Y.V. Balaso, , S.S., Shinde &, S.S. Tamboli (2016). Image compression using modified fast HAAR wavelet Transform. International Journal of Engineering Sciences & Research Technology, 5(8), 141-147.
R. C. Gonzales and R.E. Woods, (2008). Digital Image Processing (3rd Ed). Addison-Wesley.
M.I. Pu (2006). Fundamental Data Compression. Butterworth-Heinemann. London.
D . Salomon (2008) A Concise Introduction to Data Compression: Undergraduate Topics in Computer Science. Springer-Verlag London Limited.
G. Vijayvargiya,., S Silakari and R. Pandey (2103) A Survey: Various Techniques of Image Compression. International Journal of Computer Science and Information Security, 11(10).
Refbacks
- There are currently no refbacks.
Copyright (c) 2021 Journal of Electrical Engineering, Electronics, Control and Computer Science
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.