New Maximum Similarity Method for Object Identification in Photon Counting Imaging

V. Antsiperov

2021

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.

Paper Citation

in Harvard Style

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 - Volume 1: ICPRAM, ISBN 978-989-758-486-2, pages 341-348. DOI: 10.5220/0010346803410348

in Bibtex Style

@conference{icpram21,
author={V. 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 - Volume 1: ICPRAM,},
year={2021},
pages={341-348},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010346803410348},
isbn={978-989-758-486-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - New Maximum Similarity Method for Object Identification in Photon Counting Imaging
SN - 978-989-758-486-2
AU - Antsiperov V.
PY - 2021
SP - 341
EP - 348
DO - 10.5220/0010346803410348