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Author: V. E. Antsiperov

Affiliation: Kotelnikov Institute of Radioengineering and Electronics of RAS, Mokhovaya 11-7, Moscow, Russian Federation

Keyword(s): Machine Learning, Image Recognition, Photon Counting Detectors, Poisson Point Process Intensity, Precedent‒based Identification, Naive Bayes Model, Gaussian Mixture Model, K‒means Clustering.

Abstract: The paper discusses a new approach to recognition / identification of the test objects according to their intensity shape in the images registered by photon counting detectors. The main problem analyzed within the framework of the proposed approach is related to the identification decision (inference ) based on a registered set of discrete photocounts (p̃hotons) regarding the similarity of the shape of the object's intensity in the image to the shape of previously observed objects (precedents). It is shown that when the intensity shape is approximated by a mixture of Gaussian components within the framework of this approach, a recurrent identification algorithm can be synthesized, similar to the well-known K-means clustering algorithm in the machine (statistical) learning.

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Paper citation in several formats:
Antsiperov, V. (2021). New Maximum Similarity Method for Object Identification in Photon Counting Imaging. In Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-486-2; ISSN 2184-4313, SciTePress, pages 341-348. DOI: 10.5220/0010346803410348

@conference{icpram21,
author={V. E. Antsiperov.},
title={New Maximum Similarity Method for Object Identification in Photon Counting Imaging},
booktitle={Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2021},
pages={341-348},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010346803410348},
isbn={978-989-758-486-2},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - New Maximum Similarity Method for Object Identification in Photon Counting Imaging
SN - 978-989-758-486-2
IS - 2184-4313
AU - Antsiperov, V.
PY - 2021
SP - 341
EP - 348
DO - 10.5220/0010346803410348
PB - SciTePress