Land Use Classification Using Multi-neighborhood LBPs
Machine Learning
2019-02-12 v1 Machine Learning
Abstract
In this paper we propose the use of multiple local binary patterns(LBPs) to effectively classify land use images. We use the UC Merced 21 class land use image dataset. Task is challenging for classification as the dataset contains intra class variability and inter class similarities. Our proposed method of using multi-neighborhood LBPs combined with nearest neighbor classifier is able to achieve an accuracy of 77.76%. Further class wise analysis is conducted and suitable suggestion are made for further improvements to classification accuracy.
Cite
@article{arxiv.1902.03240,
title = {Land Use Classification Using Multi-neighborhood LBPs},
author = {Harjot Singh Parmar},
journal= {arXiv preprint arXiv:1902.03240},
year = {2019}
}
Comments
7 pages