Handwriting Extraction and Analysis of Signature Lists in Swiss Popular Initiatives

2026-06-03

AI Summary

This study addresses the inefficiency of manual verification processes for handwritten signatures in Swiss popular initiatives, highlighting the urgent need for automation. The authors propose the first end-to-end analysis pipeline that integrates template-based line segmentation, OCR-based text recognition, and vision-based handwriting retrieval, pioneering the application of handwriting retrieval to detect potentially duplicated submissions within signature lists. Experimental results demonstrate that generic OCR systems exhibit limited performance on short handwritten names, achieving a character error rate (CER) of 29.6%, whereas the handwriting retrieval approach shows greater promise for deduplication, attaining a mean average precision (mAP) of 50.6%. These findings validate the method’s effectiveness and novelty in supporting human reviewers during the verification process.

Abstract

Popular initiatives and referendums are central to Swiss democracy, yet the validation of handwritten signature lists remains a labor-intensive manual process. This paper investigates the potential of automated document analysis methods, including OCR and AI-based handwriting analysis, to support this task. We propose a pipeline combining template-based line segmentation with text recognition and writer retrieval techniques, evaluated on a dataset of 443 handwritten entries from 418 writers. Results show that OCR struggles with out-of-vocabulary handwriting, with a CER of 29.6% for first names. In contrast, writer retrieval performs more robustly, reaching an mAP of 50.6%. Furthermore, our experiments indicate that off-the-shelf OCR systems are not sufficiently reliable for transcription of handwritten signature data, particularly for short, out-of-vocabulary entries such as names or addresses. However, writer retrieval methods can effectively identify visually similar entries across signature lists, making them a suitable tool for supporting the detection of potential duplicate submissions based on handwriting similarity.

Problem

• handwriting extraction
• signature validation
• OCR
• writer retrieval
• popular initiatives

Innovation

• handwriting analysis
• writer retrieval
• signature validation
• OCR limitation
• template-based segmentation