Open AccessLossy codecs for digital image signatures
Author(s) -
Benjamin Kommey,
Seth Djanie Kotey,
Gideon Adom-Bamfi,
Eric Tutu Tchao
Publication year - 2021
Publication title -
sustainable engineering and innovation
Language(s) - English
Resource type - Journals
ISSN - 2712-0562
DOI - 10.37868/sei.v3i2.id144
Subject(s) - lossy compression , computer science , codec , grayscale , computer vision , thresholding , artificial intelligence , decimation , pixel , memory footprint , image quality , coding (social sciences) , image (mathematics) , computer graphics (images) , computer hardware , mathematics , statistics , filter (signal processing) , operating system
Most applications in recent times make use of images one way or the other. As physical devices for capturing images improve, the quality and sizes of images also increase. This causes a significant footprint of images on storage devices. There is ongoing research to reduce the footprint of images on storage. Since storage is a finite resource, the goal is to reduce the sizes of images while maintaining enough quality pleasant to the human eye. In this paper, the design of two lossy codecs for compressing grayscale digital signature images has been presented. The algorithms used either simple thresholding or transform coding to introduce controlled losses into the image coding chain. This was to reduce, to a great extent, the average number of bits per pixel required to represent the images. The codecs were implemented in MATLAB and experiments were conducted with test images to study the performances of the algorithms.