Show simple item record

dc.contributor.authorKittaneh, Omar
dc.date.accessioned2023-06-04T10:08:12Z
dc.date.available2023-06-04T10:08:12Z
dc.date.issued2023
dc.identifier.issn1573-7721en_US
dc.identifier.urihttp://hdl.handle.net/20.500.14131/886
dc.descriptionThis paper presents a novel image thresholding method based on multi-level entropy. The approach relies on minimizing variance entropy and is fully automated, requiring no human intervention. The method achieves segmentation results that are comparable to those obtained by the highly regarded generalized Otsu's method. Additionally, the proposed method outperforms the benchmarking generalized Kapur's method. The effectiveness of the approach is demonstrated through numerous tests on both simulated and actual images, and its performance is evaluated using various quality metrics and classification measures.en_US
dc.description.abstractThis paper proposes a new multi-level entropy-based image thresholding method. The key principle of the proposed method depends on the minimum of the variance entropy. The method is fully automated at all stages of implementation. It produces competitive segmentation results as compared to the generalized Otsu’s method, which is one of the most powerful multi-level thresholding techniques that requires human intervention. In addition, the method significantly outperforms the generalized Kapur’s method, which is one of the benchmarking entropy-based thresholding techniques. The method is successfully applied to several scenarios of trial histograms and real images, and its performance is checked using a variety of classification measures and quality metrics.en_US
dc.description.sponsorshipImage thresholding; variance entropy, truncated distributionsen_US
dc.language.isoen_USen_US
dc.titleThe variance entropy multi-level thresholding methoden_US
dc.source.journalMultimedia Tools and Applicationsen_US
dc.contributor.researcherNo Collaborationen_US
dc.contributor.labArtificial Intelligence & Cyber Security Laben_US
dc.subject.KSAMTHen_US
dc.contributor.ugstudent0en_US
dc.contributor.alumnae0en_US
dc.source.indexWoSen_US
dc.contributor.departmentNSMTUen_US
dc.contributor.pgstudent0en_US
dc.contributor.firstauthorKittaneh, Omar


This item appears in the following Collection(s)

Show simple item record