Latest Publications
Kernel Orthogonal Nonnegative Matrix Factorization: Application to Multispectral Document Image Decomposition
As a nonlinear extension of the standard nonnegative matrix factorization (NMF), kernel-based variants have demonstrated to be more effective for discovering meaningful latent features from raw data. However, many existing kernel methods allow only obtaining the basis matrix in the […]
Blind Decomposition of Multispectral Document Images Using Orthogonal Nonnegative Matrix Factorization
This paper addresses the challenge of Multispectral (MS) document image segmentation, which is an essential step for subsequent document image analysis. Most previous studies have focused only on binary (text/non-text) separation. They also rely on handcrafted features and techniques dedicated […]
Forgery Detection in Hyperspectral Document Images using Graph Orthogonal Nonnegative Matrix Factorization
The analysis of inks plays a crucial role in the examination process of questioned documents. To address this issue, we propose a new approach for ink mismatch detection in Hyperspectral […]
Feature learning for footnote-based document image classification
Classifying document images is a challenging problem that is confronted by many obstacles; specifically, the pivotal need of hand-designed features and the scarcity of labeled data. In this paper, a new approach for classifying document […]
