Abstract
Algorithms based on minimization of compactness and of fuzziness are developed whereby it is possible to obtain both fuzzy and nonfuzzy (thresholded) versions of an ill-defined image. The incorporation of fuzziness in the spatial domain, i.e., in describing the geometry of regions, makes it possible to provide more meaningful results than by considering fuzziness in grey level alone. The effectiveness of the algorithms is demonstrated for different bandwidths of the membership function using a blurred chromosome image having a bimodal histogram and a noisy tank image having a unimodal histogram as input.
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.
