LARGE-SCALE-INVARIANT TEXTURE RECOGNITION

Muhammad Rushdi, Jeffrey Ho

2011

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.

Paper Citation

in Harvard Style

Rushdi M. and Ho J. (2011). LARGE-SCALE-INVARIANT TEXTURE RECOGNITION . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2011) ISBN 978-989-8425-47-8, pages 442-445. DOI: 10.5220/0003398904420445

in Bibtex Style

@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 - Volume 1: VISAPP, (VISIGRAPP 2011)},
year={2011},
pages={442-445},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003398904420445},
isbn={978-989-8425-47-8},
}

in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2011)
TI - LARGE-SCALE-INVARIANT TEXTURE RECOGNITION
SN - 978-989-8425-47-8
AU - Rushdi M.
AU - Ho J.
PY - 2011
SP - 442
EP - 445
DO - 10.5220/0003398904420445