On the Use of Feature Descriptors on Raw Image Data

Alina Trifan, António J. R. Neves

2016

Abstract

Local feature descriptors and detectors have been widely used in computer vision in the last years for solving object detection and recognition tasks. Research efforts have been focused on reducing the complexity of these descriptors and improving their accuracy. However, these descriptors have not been tested until now on raw image data. This paper presents a study on the use of two of the most known and used feature descriptors, SURF and SIFT, directly on raw CFA images acquired by a digital camera. We are interested in understanding if the number and quality of the keypoints obtained from a raw image are comparable to the ones obtained in the grayscale images, which are normally used by these transforms. The results that we present show that the number and positions of the keypoints obtained from grayscale images are similar to the ones obtained from CFA images and furthermore to the ones obtained from grayscale images that resulted directly from the interpolation of a CFA image.

Paper Citation

in Harvard Style

Trifan A. and Neves A. (2016). On the Use of Feature Descriptors on Raw Image Data . In Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-173-1, pages 655-662. DOI: 10.5220/0005756506550662

in Bibtex Style

@conference{icpram16,
author={Alina Trifan and António J. R. Neves},
title={On the Use of Feature Descriptors on Raw Image Data},
booktitle={Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2016},
pages={655-662},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005756506550662},
isbn={978-989-758-173-1},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - On the Use of Feature Descriptors on Raw Image Data
SN - 978-989-758-173-1
AU - Trifan A.
AU - Neves A.
PY - 2016
SP - 655
EP - 662
DO - 10.5220/0005756506550662