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.
