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Authors: Muhammad Rushdi and Jeffrey Ho

Affiliation: University of Florida, United States

Keyword(s): Texture classification, Scale-invariance, Gray-level co-occurrence matrices.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computer Vision, Visualization and Computer Graphics ; Data Manipulation ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Image and Video Analysis ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Soft Computing ; Statistical Approach

Abstract: This paper addresses the problem of texture recognition across large scale variations. Most of the existing methods for texture recognition handle only small-scale variations in test images. We propose using microscopic-scale textures to classify texture images at any coarser scale without prior knowledge of the relative scale. In particular, given a test camera image, we compute the average error of approximating the test texture with patches of the microscopic texture for certain category and scaling factor. Recognition is made by selecting the category with the minimum average error over all categories and scaling factors. Experiments on camera and low-magnification microscopic images show the validity of the proposed method.

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Paper citation in several formats:
Rushdi, M. and Ho, J. (2011). LARGE-SCALE-INVARIANT TEXTURE RECOGNITION. In Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2011) - VISAPP; ISBN 978-989-8425-47-8; ISSN 2184-4321, SciTePress, pages 442-445. DOI: 10.5220/0003398904420445

@conference{visapp11,
author={Muhammad Rushdi. and Jeffrey Ho.},
title={LARGE-SCALE-INVARIANT TEXTURE RECOGNITION},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2011) - VISAPP},
year={2011},
pages={442-445},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003398904420445},
isbn={978-989-8425-47-8},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2011) - VISAPP
TI - LARGE-SCALE-INVARIANT TEXTURE RECOGNITION
SN - 978-989-8425-47-8
IS - 2184-4321
AU - Rushdi, M.
AU - Ho, J.
PY - 2011
SP - 442
EP - 445
DO - 10.5220/0003398904420445
PB - SciTePress

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