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Authors: Rodrigo D. C. da Silva ; George A. P. Thé and Fátima N. S. de Medeiros

Affiliation: Federal University of Ceara, Brazil

Keyword(s): Independent Component Analysis, Invariant Rotation, Pattern Recognition.

Related Ontology Subjects/Areas/Topics: Industrial Automation and Robotics ; Industrial Engineering ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Machine Learning in Control Applications ; Robotics and Automation ; Vision, Recognition and Reconstruction

Abstract: Independent component analysis (ICA) is a recent technique used in signal processing for feature description in classification systems, as well as in signal separation, with applications ranging from computer vision to economics. In this paper we propose a preprocessing step in order to make ICA algorithm efficient for rotation invariant feature description of images. Tests were carried out on five datasets and the extracted descriptors were used as inputs to the k-nearest neighbor (k-NN) classifier. Results showed an increasing trend on the recognition rate, which approached 100%. Additionally, when low-resolution images acquired from an industrial time-of-flight sensor are used, the recognition rate increased up to 93.33%.

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Paper citation in several formats:
da Silva, R.; A. P. Thé, G. and de Medeiros, F. (2015). Rotation-Invariant Image Description from Independent Component Analysis for Classification Purposes. In Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO; ISBN 978-989-758-123-6; ISSN 2184-2809, SciTePress, pages 210-216. DOI: 10.5220/0005512802100216

@conference{icinco15,
author={Rodrigo D. C. {da Silva}. and George {A. P. Thé}. and Fátima N. S. {de Medeiros}.},
title={Rotation-Invariant Image Description from Independent Component Analysis for Classification Purposes},
booktitle={Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO},
year={2015},
pages={210-216},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005512802100216},
isbn={978-989-758-123-6},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO
TI - Rotation-Invariant Image Description from Independent Component Analysis for Classification Purposes
SN - 978-989-758-123-6
IS - 2184-2809
AU - da Silva, R.
AU - A. P. Thé, G.
AU - de Medeiros, F.
PY - 2015
SP - 210
EP - 216
DO - 10.5220/0005512802100216
PB - SciTePress