<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Handwritten text recognition systems interpret the scanned script images as text composed of letters. In this paper, efficient offline methods using fuzzy degrees, as well as interval fuzzy degrees of type-2, are proposed to recognize letters beforehand decomposed into strokes. For such strokes, the first stage methods are used to create a set of hypotheses as to whether a group of strokes matches letter or digit patterns. Subsequently, the second-stage methods are employed to select the most promising set of hypotheses with the use of fuzzy degrees. In a primary version of the second-stage system, standard fuzzy memberships are used to measure compatibility between strokes and character patterns. As an extension of the system thus created, interval type-2 fuzzy degrees are employed to perform a selection of hypotheses that fit multiple handwriting typefaces.</p>
</abstract>

Handwritten text recognition systems interpret the scanned script images as text composed of letters. In this paper, efficient offline methods using fuzzy degrees, as well as interval fuzzy degrees of type-2, are proposed to recognize letters beforehand decomposed into strokes. For such strokes, the first stage methods are used to create a set of hypotheses as to whether a group of strokes matches letter or digit patterns. Subsequently, the second-stage methods are employed to select the most promising set of hypotheses with the use of fuzzy degrees. In a primary version of the second-stage system, standard fuzzy memberships are used to measure compatibility between strokes and character patterns. As an extension of the system thus created, interval type-2 fuzzy degrees are employed to perform a selection of hypotheses that fit multiple handwriting typefaces.

Handwritten Word Recognition Using Fuzzy Matching Degrees

Department of Computer, Control and Management Engineering

Journal of Artificial Intelligence and Soft Computing Research

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Handwritten Word Recognition Using Fuzzy Matching Degrees"}

Handwritten text recognition systems interpret the scanned script images as text composed of letters. In this paper, efficient offline methods using fuzzy...

Handwritten Word Recognition Using Fuzzy Matching Degrees

Publié en ligne: 29 mai 2021

Pages: 229 - 242

Reçu: 07 sept. 2020

Accepté: 16 avr. 2021

DOI: https://doi.org/10.2478/jaiscr-2021-0014

Mots clés
offline handwriting recognition, handwritten strokes, fuzzy matching degrees, interval type-2 fuzzy sets, decision trees, bigram frequency

© 2021 Michał Wróbel et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Handwritten Word Recognition Using Fuzzy Matching Degrees

Publié en ligne: 29 mai 2021

Pages: 229 - 242

Reçu: 07 sept. 2020

Accepté: 16 avr. 2021

DOI: https://doi.org/10.2478/jaiscr-2021-0014

Mots clésoffline handwriting recognition, handwritten strokes, fuzzy matching degrees, interval type-2 fuzzy sets, decision trees, bigram frequency

© 2021 Michał Wróbel et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Mots clés
offline handwriting recognition, handwritten strokes, fuzzy matching degrees, interval type-2 fuzzy sets, decision trees, bigram frequency