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Segmentation of scanning-transmission electron microscopy images using the ordered median problem

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URI: http://hdl.handle.net/10498/26920

DOI: 10.1016/j.ejor.2022.01.022

ISSN: 0377-2217

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APC_2022_005.pdf (2.755Mb)
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Author/s
Calvino Gámez, José JuanAuthority UCA; López Haro, MiguelAuthority UCA; Muñoz Ocaña, Juan ManuelAuthority UCA; Puerto, Justo; Rodríguez Chía, Antonio ManuelAuthority UCA
Date
2022
Department
Ciencia de los Materiales e Ingeniería Metalúrgica y Química Inorgánica; Estadística e Investigación Operativa
Source
European Journal of Operational Research, Vol. 302, Núm. 2, pp. 671-687
Abstract
This paper presents new models for segmentation of 2D and 3D Scanning-Transmission Electron Micro- scope images based on the ordered median function. The main advantage of using this function is its good adaptability to the different types of images to be studied due to the wide range of weight vec- tors that can be cast. Classical segmentation models stand out for their ability to provide a segmentation of the original image very quickly and with low computational burden. However, they do not usually achieve high quality segmentations with a small number of clusters in order to classify the different ele- ments which compose the structure represented in the image. The quality of the segmentation provided by our approach is analysed using different choices of the weight vector in some real instances. More- over, improvements are proposed for the formulations to reduce the computational time needed to solve these problems by taking advantage of the weight vector structure
Subjects
Location; Ordered median function; Segmentation; Clustering; Mixed integer linear programming
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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
This work is under a Creative Commons License Attribution-NonCommercial-NoDerivatives 4.0 Internacional

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