Extract an essential skeleton of a character as a graph from a character image

TL;DR

This paper introduces a novel method combining Growing Neural Gas and Relative Network Graph algorithms to extract skeleton graphs from character images, including distorted and handwritten ones, facilitating feature extraction for recognition.

Contribution

It presents a new approach that effectively extracts character skeletons as graphs using GNG and RNG, improving robustness to noise and distortions.

Findings

Successfully extracted skeleton graphs from noisy and handwritten characters.

Demonstrated robustness of the method in various distorted images.

Enhanced feature extraction for character recognition tasks.

Abstract

This paper aims to make a graph representing an essential skeleton of a character from an image that includes a machine printed or a handwritten character using growing neural gas (GNG) method and relative network graph (RNG) algorithm. The visual system in our brain can recognize printed characters and handwritten characters easily, robustly, and precisely. How does our brain robustly recognize characters? The visual processing in our brain uses the essential features of an object, such as crosses and corners. These features will be helpful for character recognition by a computer. However, extraction of the features is difficult. If the skeleton of a character is represented as a graph, we can more easily extract the features. To extract the skeleton of a character as a graph from an image, this paper proposes the new approach using GNG and RNG algorithm. I achieved to extract skeleton graphs from images including distorted, noisy, and handwritten characters.