Stamp processing with examplar features

TL;DR

This paper introduces an unsupervised shape-based method for automatic stamp verification and detection in document images, leveraging minimal training data to learn effective shape representations.

Contribution

It presents a novel unsupervised clustering approach for shape feature learning tailored to stamp detection in document digitization.

Findings

Effective in challenging scenarios

Requires only a small set of training images

Demonstrates robust stamp verification and detection

Abstract

Document digitization is becoming increasingly crucial. In this work, we propose a shape based approach for automatic stamp verification/detection in document images using an unsupervised feature learning. Given a small set of training images, our algorithm learns an appropriate shape representation using an unsupervised clustering. Experimental results demonstrate the effectiveness of our framework in challenging scenarios.