Image Analysis Based on Nonnegative/Binary Matrix Factorization
Computer Vision and Pattern Recognition
2020-07-03 v1 Statistical Mechanics
Abstract
Using nonnegative/binary matrix factorization (NBMF), a matrix can be decomposed into a nonnegative matrix and a binary matrix. Our analysis of facial images, based on NBMF and using the Fujitsu Digital Annealer, leads to successful image reconstruction and image classification. The NBMF algorithm converges in fewer iterations than those required for the convergence of nonnegative matrix factorization (NMF), although both techniques perform comparably in image classification.
Cite
@article{arxiv.2007.00889,
title = {Image Analysis Based on Nonnegative/Binary Matrix Factorization},
author = {Hinako Asaoka and Kazue Kudo},
journal= {arXiv preprint arXiv:2007.00889},
year = {2020}
}
Comments
3 pages, 1 figure