Region Merging Strategy Using Statistical Analysis for Interactive Image Segmentation on Dental Panoramic Radiographs

Agus Zainal Arifin and Rarasmaya Indraswari and Nanik Suciati and Eha Renwi Astuti and Dini Adni Navastara (2017) Region Merging Strategy Using Statistical Analysis for Interactive Image Segmentation on Dental Panoramic Radiographs. International Review on Computers and Software (I.RE.CO.S.), 12 (1). pp. 64-74. ISSN 1828-6003

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Abstract

Abstract – In low contrast images such as dental panoramic radiographs, the optimum parameters for automatic image segmentation is not easily determined. Semi-automatic image segmentation which is interactively guided by user is one alternative that could provide a good segmentation results. In this paper we proposed a novel strategy of region merging in interactive image segmentation using discriminant analysis on dental panoramic radiographs. A new similarity measurement among regions is introduced. This measurement merges regions which have minimal inter-class variance either with object or background cluster. Since the representative sample regions are selected by user, the similarity between merged regions with the corresponded samples could be preserved. Experimental results show that the proposed region merging strategy give a high segmentation accuracy both for low contrast and natural images.

Item Type: Article
Subjects: R Medicine
R Medicine > RK Dentistry
Divisions: 02. Fakultas Kedokteran Gigi
Creators:
CreatorsNIM
Agus Zainal Arifin-
Rarasmaya Indraswari-
Nanik Suciati-
Eha Renwi AstutiNIDN0013056102
Dini Adni Navastara-
Depositing User: Rudy Febiyanto
Date Deposited: 26 Jun 2021 12:46
Last Modified: 26 Jun 2021 12:46
URI: http://repository.unair.ac.id/id/eprint/107778
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