An Autoencoder Based ASCII Art Generator

Masaomi Kimura, Mohammad Iqbal, Imam Mukhlash

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

ASCII art is a way to represent an image with character shapes. It is common to carry ASCII art instead of displaying image files on Internet bulletin boards. Multibyte encodings contain various characters that are useful to shape an image. The essential idea required to get ASCII art is to approximate color distribution at the portion of a target image to a character shape. In this study, we make a machine learning model that learns the shapes of characters in a multibyte encoding to convert a partial image of a target image to a font image.

Original languageEnglish
Title of host publicationICIIT 2023 - Proceedings of 2023 8th International Conference on Intelligent Information Technology
PublisherAssociation for Computing Machinery
Pages106-111
Number of pages6
ISBN (Electronic)9781450399616
DOIs
Publication statusPublished - 2023 Feb 24
Event8th International Conference on Intelligent Information Technology, ICIIT 2023 - Hybrid, Da Nang, Viet Nam
Duration: 2023 Feb 242023 Feb 26

Publication series

NameACM International Conference Proceeding Series

Conference

Conference8th International Conference on Intelligent Information Technology, ICIIT 2023
Country/TerritoryViet Nam
CityHybrid, Da Nang
Period23/2/2423/2/26

Keywords

  • ASCII art synthesis
  • autoencoder
  • deep learning
  • K-nearest neighborhood

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

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