Image Labeling by Integrating Global Information by 7 Patches and Local Information

Takuto Omiya, Takahiro Ishida, Kazuhiro Hotta

2015

Abstract

We propose an image labeling method by integrating the probabilities of local and global information. Many conventional methods put label to each pixel or region by using the features extracted from local regions and local contextual relationships between neighboring regions. However, labeling results tend to depend on a local viewpoint. To overcome this problem, we propose the image labeling method using not only local information but also global information. The probability by global information is estimated by KNearest Neighbor. In the experiments using the MSRC21 dataset, labeling accuracy is much improved by using global information.

Paper Citation

in Harvard Style

Omiya T., Ishida T. and Hotta K. (2015). Image Labeling by Integrating Global Information by 7 Patches and Local Information . In Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2015) ISBN 978-989-758-090-1, pages 536-541. DOI: 10.5220/0005356005360541

in Bibtex Style

@conference{visapp15,
author={Takuto Omiya and Takahiro Ishida and Kazuhiro Hotta},
title={Image Labeling by Integrating Global Information by 7 Patches and Local Information},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2015)},
year={2015},
pages={536-541},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005356005360541},
isbn={978-989-758-090-1},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2015)
TI - Image Labeling by Integrating Global Information by 7 Patches and Local Information
SN - 978-989-758-090-1
AU - Omiya T.
AU - Ishida T.
AU - Hotta K.
PY - 2015
SP - 536
EP - 541
DO - 10.5220/0005356005360541