Název:	Automated Microwave Tomography (MWT) Image Segmentation: State-of-the-Art Implementation and Evaluation
Autoři:	Zhang, Yuchong Ma, Yong Adel, Omrani Yadav, Rahul Fjeld, Morten Fratarcangeli, Marco
Citace zdrojového dokumentu:	WSCG 2020: full papers proceedings: 28th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, p. 126-136.
Datum vydání:	2020
Nakladatel:	Václav Skala - UNION Agency
Typ dokumentu:	conferenceObject konferenční příspěvek
URI:	http://wscg.zcu.cz/WSCG2020/2020-CSRN-3001.pdf http://hdl.handle.net/11025/38459
ISBN:	978-80-86943-35-0
ISSN:	2464–4617 (print) 2464–4625 (CD-ROM)
Klíčová slova:	segmentace obrazu;Otsu;k-znamená;mikrovlnná tomografie
Klíčová slova v dalším jazyce:	image segmentation;Otsu;K-means;microwave tomography
Abstrakt v dalším jazyce:	Inspired by the high performance in image-based medical analysis, this paper explores the use of advanced segmentation techniques for industrial Microwave Tomography (MWT). Our context is the visual analysis of moisture levels in porous foams undergoing microwave drying. We propose an automatic segmentation technique—MWT Segmentation based on K-means (MWTS-KM) and demonstrate its efficiency and accuracy for industrial use. MWTS-KM consists of three stages: image augmentation, grayscale conversion, and K-means implementation. To estimate the performance of this technique, we empirically benchmark its efficiency and accuracy against two well-established alternatives: Otsu and K-means. To elicit performance data, three metrics (Jaccard index, Dice coefficient and false positive) are used. Our results indicate that MWTS-KM outperforms the well-established Otsu and K-means, both in visually observable and objectively quantitative evaluation.
Práva:	© Václav Skala - UNION Agency
Vyskytuje se v kolekcích:	WSCG 2020: Full Papers Proceedings

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