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Authors: M. Righi 1 ; M. D’Acunto 2 and O. Salvetti 1

Affiliations: 1 ISTI-CNR, NanoICT Laboratory and Area della Ricerca CNR Pisa, Italy ; 2 ISTI-CNR, ISM-CNR, NanoICT Laboratory and Area della Ricerca CNR Pisa, Italy

Keyword(s): pattern recognition, image analysis, image segmentation, boundary detection, graph partitioning algorithm

Abstract: Recently, we have suggested a simple and general-purpose method able to combine high-resolution analysis with the classification and identification of components of microscopy imaging. The method named PRIAR (Pattern Recognition Image Augumented Resolution) is a tool developed by the authors that gives the possibility to enhance spatial and photometric resolution of low-res images. The implemented algorithm follows the scheme: 1) image classification; 2) blind super-resolution on single frame; 3) pattern-analysis; 4) reconstruction of the discovered pattern. In this paper, we suggest some improvements of the PRIAR algorithm, in particular, the definition of a segmentation method which is based on homomorphism between a processed image and a graph describing the image itself, able to identify object of interest in complex patterns. The case study is the identification of organs inside biological cells acquired with Atomic Force Microscopy Technique.

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Paper citation in several formats:
Righi, M.; D’Acunto, M. and Salvetti, O. (2015). PRIAR using a Graph Segmentation Method. In Proceedings of the 5th International Workshop on Image Mining. Theory and Applications (VISIGRAPP 2015) - IMTA-5; ISBN 978-989-758-094-9, SciTePress, pages 46-52. DOI: 10.5220/0005461600460052

@conference{imta-515,
author={M. Righi. and M. D’Acunto. and O. Salvetti.},
title={PRIAR using a Graph Segmentation Method},
booktitle={Proceedings of the 5th International Workshop on Image Mining. Theory and Applications (VISIGRAPP 2015) - IMTA-5},
year={2015},
pages={46-52},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005461600460052},
isbn={978-989-758-094-9},
}

TY - CONF

JO - Proceedings of the 5th International Workshop on Image Mining. Theory and Applications (VISIGRAPP 2015) - IMTA-5
TI - PRIAR using a Graph Segmentation Method
SN - 978-989-758-094-9
AU - Righi, M.
AU - D’Acunto, M.
AU - Salvetti, O.
PY - 2015
SP - 46
EP - 52
DO - 10.5220/0005461600460052
PB - SciTePress

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