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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
