Image Processing, Computer Vision, Data Visualization, and Data Mining for Transdisciplinary Visual Communication: What Are the Differences and Which Should or Could You Use?
Richard S. Segall
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Richard S. Segall
Department of Information Systems & Business Analytics, Neil Griffin College of Business, Arkansas State University, State University, Arkansas, United States
Cite this paper as:Segall, R. S. (2024). Image Processing, Computer Vision, Data Visualization, and Data Mining for Transdisciplinary Visual Communication: What Are the Differences and Which Should or Could You Use?.
Journal of Systemics, Cybernetics and Informatics, 22(7), 85-92. https://doi.org/10.54808/JSCI.22.07.85
Online ISSN (Journal): 1690-4524
Abstract
Data can be for any discipline, and is only useful if presented, processed, or analyzed in meaningful ways. There are many formats for data such as text, numerical, image and ultrasound. Data can be disciple specific and instrument specific. Applications can be for medical, data communication, remote sensing, astronomical, geospatial and other. This paper discusses what are the differences in purposes, inputs and performing certain operations to get some useful information from its outputs, and applications between: (1.) Image Processing, (2.) Computer Vision, (3.) Data Visualization and (4.) Data Mining. What are these different techniques, and how would you determine which to use for your available data or circumstances? Illustrations of recent studies for each are presented.
