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dc.contributor.authorWonohadidjojo, Daniel Martomanggolo
dc.date.accessioned2018-02-26T07:10:10Z
dc.date.available2018-02-26T07:10:10Z
dc.date.issued2017-03-01
dc.identifier.issn2476-907X
dc.identifier.urihttps://dspace.uc.ac.id/handle/123456789/1215
dc.description.abstractIn this research, the researcher presents the enhancement method of cells images. The first method used in the local contrast enhancement is Intuitionistic Fuzzy Sets (IFS). The proposed method is the IFS optimized by Artificial Bee Colony (ABC) algorithm. The ABC is used to optimize the membership function parameter of IFS. To measure the image quality, Image Enhancement Metric (IEM) is applied. The results of local contrast enhancement using both methods are compared with the results using histogram equalization method. The tests are conducted using two MDCK cell images. The results of local contrast enhancement using both methods are evaluated by observing the enhanced images and IEM values. The results show that the methods outperform the histogram equalization method. Furthermore, the method using IFS-ABC is better than the IFS method.en_US
dc.language.isoen_USen_US
dc.publisherBina Nusantara Universityen_US
dc.subjectLocal contrast enhancement, Cell, Intuitionistic Fuzzy Sets, Artificial Bee Colony Algorithmen_US
dc.titleLocal Contrast Enhancement Using Intuitionistic Fuzzy Sets Optimized By Artificial Bee Colony Algorithmen_US
dc.typeOtheren_US


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