Handwriting Extraction and Analysis of Signature Lists in Swiss Popular Initiatives

• URL: http://arxiv.org/abs/2606.05018v1
• Date: Wed, 03 Jun 2026 15:41:30 GMT
• Title: Handwriting Extraction and Analysis of Signature Lists in Swiss Popular Initiatives
• Abstract summary: Off-the-shelf OCR systems are not sufficiently reliable for transcription of handwritten signature data.<n>Writer retrieval methods can effectively identify visually similar entries across signature lists.
• Score: 3.1565960088761784
• License: http://creativecommons.org/licenses/by/4.0/
• 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.

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