A Robust Descriptor for Color Texture Classification Under Varying Illumination

Tamiris Negri, Fang Zhou, Zoran Obradovic, Adilson Gonzaga

2017

Abstract

Classifying color textures under varying illumination sources remains challenging. To address this issue, this paper introduces a new descriptor for color texture classification, which is robust to changes in the scene illumination. The proposed descriptor, named Color Intensity Local Mapped Pattern (CILMP), incorporates relevant information about the color and texture patterns from the image in a multiresolution fashion. The CILMP descriptor explores the color features by comparing the magnitude of the color vectors inside the RGB cube. The proposed descriptor is evaluated on nine experiments over 50,048 images of raw food textures acquired under 46 lighting conditions. The experimental results have shown that CILMP performs better than the state-of-the-art methods, reporting an increase (up to $20.79) in the classification accuracy, compared to the second-best descriptor. In addition, we concluded from the experimental results that the multiresolution analysis improves the robustness of the descriptor and increases the classification accuracy.

Paper Citation

in Harvard Style

Negri T., Zhou F., Obradovic Z. and Gonzaga A. (2017). A Robust Descriptor for Color Texture Classification Under Varying Illumination . In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017) ISBN 978-989-758-225-7, pages 378-388. DOI: 10.5220/0006143403780388

in Bibtex Style

@conference{visapp17,
author={Tamiris Negri and Fang Zhou and Zoran Obradovic and Adilson Gonzaga},
title={A Robust Descriptor for Color Texture Classification Under Varying Illumination},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017)},
year={2017},
pages={378-388},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006143403780388},
isbn={978-989-758-225-7},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017)
TI - A Robust Descriptor for Color Texture Classification Under Varying Illumination
SN - 978-989-758-225-7
AU - Negri T.
AU - Zhou F.
AU - Obradovic Z.
AU - Gonzaga A.
PY - 2017
SP - 378
EP - 388
DO - 10.5220/0006143403780388