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Memetic Computing
Erschienen in: Memetic Computing 4/2013

01.12.2013 | Regular research paper

Bi-level thresholding using PSO, Artificial Bee Colony and MRLDE embedded with Otsu method

verfasst von: Sushil Kumar, Pravesh Kumar, Tarun Kumar Sharma, Millie Pant

Erschienen in: Memetic Computing | Ausgabe 4/2013

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Abstract

Image segmentation is required to be studied in detail some particular features (areas of interest) of a digital image. It forms an important and exigent part of image processing and requires an exhaustive and robust search technique for its implementation. In the present work we have studied the working of MRLDE, a newly proposed variant of differential evolution combined with Otsu method, a well known image segmentation method for bi-level thresholding. The proposed variant, termed as Otsu+MRLDE, is tested on a set of 10 images and the results are compared with Otsu method and some other well known metaheuristics.
Vorheriger Artikel Design and simulation of FIR band pass and band stop filters using gravitational search algorithm

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Metadaten
Titel
Bi-level thresholding using PSO, Artificial Bee Colony and MRLDE embedded with Otsu method
verfasst von
Sushil Kumar
Pravesh Kumar
Tarun Kumar Sharma
Millie Pant
Publikationsdatum
01.12.2013
Verlag
Springer Berlin Heidelberg
Erschienen in
Memetic Computing / Ausgabe 4/2013
Print ISSN: 1865-9284
Elektronische ISSN: 1865-9292
DOI
https://doi.org/10.1007/s12293-013-0123-5

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