Capturing More: Learning Multi-Domain Representations for Robust Online Handwriting Verification

TL;DR

This paper introduces SPECTRUM, a novel multi-domain model for online handwriting verification that combines temporal and frequency features to improve accuracy and robustness over traditional methods.

Contribution

The paper presents a new multi-domain learning framework with a multi-scale interactor and self-gated fusion module, advancing the state-of-the-art in online handwriting verification.

Findings

SPECTRUM outperforms existing OHV methods in accuracy.

Multi-domain learning enhances discriminative power of handwriting features.

Incorporating multiple biometrics improves verification robustness.

Abstract

In this paper, we propose SPECTRUM, a temporal-frequency synergistic model that unlocks the untapped potential of multi-domain representation learning for online handwriting verification (OHV). SPECTRUM comprises three core components: (1) a multi-scale interactor that finely combines temporal and frequency features through dual-modal sequence interaction and multi-scale aggregation, (2) a self-gated fusion module that dynamically integrates global temporal and frequency features via self-driven balancing. These two components work synergistically to achieve micro-to-macro spectral-temporal integration. (3) A multi-domain distance-based verifier then utilizes both temporal and frequency representations to improve discrimination between genuine and forged handwriting, surpassing conventional temporal-only approaches. Extensive experiments demonstrate SPECTRUM's superior performance over existing OHV methods, underscoring the effectiveness of temporal-frequency multi-domain learning. Furthermore, we reveal that incorporating multiple handwritten biometrics fundamentally enhances the discriminative power of handwriting representations and facilitates verification. These findings not only validate the efficacy of multi-domain learning in OHV but also pave the way for future research in multi-domain approaches across both feature and biometric domains. Code is publicly available at https://github.com/NiceRingNode/SPECTRUM.