Gini index-based digital image complementing in the study of medical images

Article type: Research Article

Authors: A-iyeh, Enoch^a | Peters, James F.^{a; b; *}

Affiliations: [a] Computational Intelligence Laboratory, Department of Electrical & Computer Engineering, University of Manitoba, Winnipeg, MB, Canada | [b] Department of Mathematics, Adiyaman University, Adiyaman, Turkey

Correspondence: [*] Corresponding author: James F. Peters, Computational Intelligence Laboratory, Department of Electrical & Computer Engineering, University of Manitoba, E1-526, 75A Chancellor's Circle, Winnipeg, MB R3T 5V6, Canada. E-mail: jfpeters@ee.umanitoba.ca

Abstract: The focus of this article is on Gini Index-based image complementing that utilises the relative frequency of occurrence of pixel intensities in digital images. The outcome of the proposed approach to image complementing is that the transformation function maps a complemented image to a shape that is usually not a straight line based on pixels and image information. The proposed approach lends support to decision-making in image analysis and image understanding. A practical application of the proposed to image complementing is given in terms of the analysis of medical images.

Keywords: Complementing, Gini index, image analysis, medical images, relative frequency

DOI: 10.3233/IDT-140217

Journal: Intelligent Decision Technologies, vol. 9, no. 2, pp. 209-218, 2015