Skip to content
Publish & Distribute
Publishing Solutions
Distribution Solutions
Library Services
Subjects
Architecture and Design
Arts
Business and Economics
Chemistry
Classical and Ancient Near Eastern Studies
Computer Sciences
Cultural Studies
Engineering
General Interest
Geosciences
History
Industrial Chemistry
Jewish Studies
Law
Library and Information Science, Book Studies
Life Sciences
Linguistics and Semiotics
Literary Studies
Materials Sciences
Mathematics
Medicine
Music
Pharmacy
Philosophy
Physics
Social Sciences
Sports and Recreation
Theology and Religion
Publications
Journals
Books
Proceedings
Publishers
Journal Matcher
Blog
Contact
Search
English
English
Deutsch
Polski
Español
Français
Italiano
Cart
Home
Journals
International Journal on Smart Sensing and Intelligent Systems
Volume 13 (2020): Issue 1 (January 2020)
Open Access
Indonesian traffic sign detection based on Haar-PHOG features and SVM classification
Aris Sugiharto
Aris Sugiharto
Department of Computer Science/Informatics, Universitas Diponegoro
Semarang, Indonesia
Search for this author on
Sciendo
|
Google Scholar
Sugiharto, Aris
,
Agus Harjoko
Agus Harjoko
Department of Computer Science and Electronics, Universitas Gadjah Mada
Yogyakarta, Indonesia
Search for this author on
Sciendo
|
Google Scholar
Harjoko, Agus
and
Suharto Suharto
Suharto Suharto
Department of Computer Science and Electronics, Universitas Gadjah Mada
Yogyakarta, Indonesia
Search for this author on
Sciendo
|
Google Scholar
Suharto, Suharto
Oct 05, 2020
International Journal on Smart Sensing and Intelligent Systems
Volume 13 (2020): Issue 1 (January 2020)
About this article
Previous Article
Next Article
Abstract
Article
Figures & Tables
References
Authors
Articles in this Issue
Preview
PDF
Cite
Share
Download Cover
Article Category:
Research-Article
Published Online:
Oct 05, 2020
Page range:
1 - 15
Received:
Jun 03, 2020
DOI:
https://doi.org/10.21307/ijssis-2020-026
Keywords
Haar–PHOG
,
HOG
,
PHOG
,
SVM
,
Traffic signs
© 2020 Aris Sugiharto et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
