Work

HAnnoI: A Handwriting Annotation Interface to Extract Data for Linguistic Analyses of Graphetic Detail

Year: 2026

Type: conference-paper

Abstract: In this paper, we present HAnnoI -short for Handwriting Annotation Interface -, an open-source GUI application developed in Python that allows its users to identify and annotate so-called Regions of Interest (ROIs) within digital images.Several meta data such as their coordinates are retained for each ROI and they can be annotated on user-defined annotation layers.HAnnoI comes with a function to export all annotations to a CSV file, enabling further processing as well as quantitative analyses.HAnnoI also has a function to extract single PNG image files of all ROIs.It was developed to mark and annotate single letters in scans of handwritten (alphabetic) texts for linguistic analyses, yet it is not limited to this particular use case.In this paper, we first provide information on HAnnoI's conception and technical details as well as an overview of alternative applications.We then showcase HAnnoI's capabilities in a letter annotation task, where five annotators marked instances of lower case in handwritten texts.Finally, we report on an exploratory analysis of this data, showing what kinds of investigations are enabled by using HAnnoI.The tool is available for free use at https://github.com/pywielR/HAnnoI.

Source: Language Resources and Evaluation Conference (LREC)

DOI: 10.63317/2i7h8bznd292

Authors: Joshua Wieler, Simon Petitjean, Kristian Berg, Henriette Huber, Stefan Hartmann

Institutions: Carl von Ossietzky Universität Oldenburg, Ruhr University Bochum, Heinrich Heine University Düsseldorf

Language: English

Topic: Handwritten Text Recognition Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funder: Deutsche Forschungsgemeinschaft

Award: Wie sich Morphologie materialisiert: Formen und Grenzen in spontanschriftlicher Sprache