A new method for segmentation of microscopic blood cell images by using histogram based automatic thresholding

dc.contributor.author	Coteli, R. and Tuncer, T. and Avci, E. and Ustundag, M. and Dogantekin, E. and Dogantekin, A.
dc.date.accessioned	2021-04-08T12:08:02Z
dc.date.available	2021-04-08T12:08:02Z
dc.date.issued	2017
dc.identifier.issn	18426573
dc.identifier.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85030659965&partnerID=40&md5=2abb84acd4e408bab6d9cfeb20e5b915
dc.identifier.uri	http://acikerisim.bingol.edu.tr/handle/20.500.12898/4495
dc.description.abstract	In this study, a novel thresholding algorithm based on histogram shape (TAHS) is proposed for determining the multiple thresholding. In the proposed thresholding method, histogram is divided into smaller windows with same size. In the proposed method, the biggest difference between pixel intensities is found. The proposed method is applied to blood cell images and is compared with Otsu method for a better validation. Advantage of the proposed method is that one or more thresholding points can be obtained. Therefore, objects with different spatial feature can be detected successfully. The experimental studies show that TAHS method gives satisfactory thresholding results. © 2017, National Institute of Optoelectronics. All rights reserved.
dc.language.iso	English
dc.source	Optoelectronics and Advanced Materials, Rapid Communications
dc.title	A new method for segmentation of microscopic blood cell images by using histogram based automatic thresholding

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