Famous Companies Use More Letters in Logo: A Large-Scale Analysis of Text Area in Logo

Shintaro Nishi, Takeaki Kadota, Seiichi Uchida

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

Abstract

This paper analyzes a large number of logo images from the LLD-logo dataset, by recent deep learning-based techniques, to understand not only design trends of logo images and but also the correlation to their owner company. Especially, we focus on three correlations between logo images and their text areas, between the text areas and the number of followers on Twitter, and between the logo images and the number of followers. Various findings include the weak positive correlation between the text area ratio and the number of followers of the company. In addition, deep regression and deep ranking methods can catch correlations between the logo images and the number of followers.

Original languageEnglish
Title of host publicationDocument Analysis and Recognition – ICDAR 2021 Workshops - Proceedings
EditorsElisa H. Barney Smith, Umapada Pal
PublisherSpringer Science and Business Media Deutschland GmbH
Pages97-111
Number of pages15
ISBN (Print)9783030861971
DOIs
Publication statusPublished - 2021
EventInternational Workshops co-located with the 16th International Conference on Document Analysis and Recognition, ICDAR 2021 - Lausanne, Switzerland
Duration: Sep 5 2021Sep 10 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12916 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Workshops co-located with the 16th International Conference on Document Analysis and Recognition, ICDAR 2021
Country/TerritorySwitzerland
CityLausanne
Period9/5/219/10/21

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint

Dive into the research topics of 'Famous Companies Use More Letters in Logo: A Large-Scale Analysis of Text Area in Logo'. Together they form a unique fingerprint.

Cite this