Stroke Segmentation of Handwritten Text Based on Medial Representation

The paper deals with structural analysis of handwritten text by digital binary images. A new approach to structural analysis is proposed. It consists in representing text image as strokes, a set of calligraphic elements. The method of stroke segmentation of handwritten text is based on the medial representation of a binary image in the form of a continuous skeleton and a radial function. Each stroke is assumed to be a trace of pen movement. The stroke description includes static and dynamic components. The static components of strokes are cycles and chains—subgraphs of the skeleton graph. The dynamic components are the description of strokes as paths of pen movement including the starting point and direction of the movement.

Authors

Institutions

Publication Details

Journal
Pattern Recognition and Image Analysis
Published
2024-12-01
DOI
https://doi.org/10.1134/s1054661824701256
Primary Topic
Handwritten Text Recognition Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Stroke Segmentation of Handwritten Text Based on Medial Representation

Leonid Mestetskiy
Pattern Recognition and Image Analysis
Handwritten Text Recognition Techniques
article

Stroke Segmentation of Handwritten Text Based on Medial Representation

Leonid Mestetskiy
article en

Abstract

The paper deals with structural analysis of handwritten text by digital binary images. A new approach to structural analysis is proposed. It consists in representing text image as strokes, a set of calligraphic elements. The method of stroke segmentation of handwritten text is based on the medial representation of a binary image in the form of a continuous skeleton and a radial function. Each stroke is assumed to be a trace of pen movement. The stroke description includes static and dynamic components. The static components of strokes are cycles and chains—subgraphs of the skeleton graph. The dynamic components are the description of strokes as paths of pen movement including the starting point and direction of the movement.

Pattern Recognition and Image AnalysisVol. 34(4)
Lomonosov Moscow State University (RU)
Openalex Percentile: Top 71%
Handwritten Text Recognition Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.