Oil Portrait Snapshot Classification on Mobile

Yan Sun, Xiaomu Niu

2017

Abstract

In recent years, several art museums have developed smartphone applications as the e-guide in museums. However few of them provide the function of instant retrieval and identification for a painting snapshot taken by mobile. Therefore in this work we design and implement an oil portrait classification application on smartphone. The accuracy of recognition suffers greatly by aberration, blur, geometric deformation and shrinking due to the unprofessional quality of snapshots. Low-megapixel phone camera is another factor downgrading the classification performance. Carefully studying the nature of such photos, we adopts the SIPH algorithm (Scale-invariant feature transform based Image Perceptual Hashing)) to extract image features and generate image information digests. Instead of popular conventional Hamming method, we applied an effective method to calculate the perceptual distance. Testing results show that the proposed method conducts satisfying performance on robustness and discriminability in portrait snapshot identification and feature indexing.

Paper Citation

in Harvard Style

Sun Y. and Niu X. (2017). Oil Portrait Snapshot Classification on Mobile . 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 143-149. DOI: 10.5220/0006082401430149

in Bibtex Style

@conference{visapp17,
author={Yan Sun and Xiaomu Niu},
title={Oil Portrait Snapshot Classification on Mobile},
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={143-149},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006082401430149},
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 - Oil Portrait Snapshot Classification on Mobile
SN - 978-989-758-225-7
AU - Sun Y.
AU - Niu X.
PY - 2017
SP - 143
EP - 149
DO - 10.5220/0006082401430149