An approach to classify traffic signs categories with traditional method
Author
Source
Iraqi Journal for Information Technology
Issue
Vol. 8, Issue 3 (30 Jun. 2018), pp.153-178, 26 p.
Publisher
Iraqi Association of Information Technology
Publication Date
2018-06-30
Country of Publication
Iraq
No. of Pages
26
Main Subjects
Abstract EN
Classification of groups of traffic signs like, (Control, Command, Prohibition, Reservation, Comprehensive, Selective Restriction, Traffic Signals, Warning, Information, and Guidance groups of signs) according to British standard classification is done by decomposition colors in traffic sign images using new color recognition approach by detection of RGB British standard traffic sign, these colors are White, Black, Yellow, Orange, Red, Brown, Light Green, Dark Green and Blue with predefined range around the standard RGB color, redefine image according to largest frequency of color while remove White and Black colors, convert mono color image consecutively to gray, black and white, estimating edges using Sobel method, reconstruct boundaries, and find fast Fourier transformation (FFT), use ten coefficients with ten categories to train classical structure neural network with thousands of traffic signs, simulate with tens of them and estimate efficiency of the system.
American Psychological Association (APA)
al-Zuhairy, Ahmad Salih Mahdi. 2018. An approach to classify traffic signs categories with traditional method. Iraqi Journal for Information Technology،Vol. 8, no. 3, pp.153-178.
https://search.emarefa.net/detail/BIM-916167
Modern Language Association (MLA)
al-Zuhairy, Ahmad Salih Mahdi. An approach to classify traffic signs categories with traditional method. Iraqi Journal for Information Technology Vol. 8, no. 3 (2018), pp.153-178.
https://search.emarefa.net/detail/BIM-916167
American Medical Association (AMA)
al-Zuhairy, Ahmad Salih Mahdi. An approach to classify traffic signs categories with traditional method. Iraqi Journal for Information Technology. 2018. Vol. 8, no. 3, pp.153-178.
https://search.emarefa.net/detail/BIM-916167
Data Type
Journal Articles
Language
English
Record ID
BIM-916167