Traffic sign recognition by using chain code

The Traffic signs are considered as Traffic Safety tools, Because of their role in the organization of traffic and vehicles to insure the safety of the passengers, pedestrians and the structures of traffic signs are very important devices which help the drivers to drive in safety and adequate manner...

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Bibliographic Details
Main Authors: Sundus Ebraheem, Reham Al-Atiwi
Format: Article
Language:Arabic
Published: Mosul University 2012-12-01
Series:Al-Rafidain Journal of Computer Sciences and Mathematics
Subjects:
Online Access:https://csmj.mosuljournals.com/article_163722_5b3b06a16db0487b0b80f5437625a3d6.pdf
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spelling doaj-5de2923408df49e38ce907f361778f492020-11-25T04:06:40ZaraMosul UniversityAl-Rafidain Journal of Computer Sciences and Mathematics 1815-48162311-79902012-12-019211312610.33899/csmj.2012.163722163722Traffic sign recognition by using chain codeSundus Ebraheem0Reham Al-Atiwi1College of Computer Sciences and Mathematics University of Mosul, Mosul, IraqCollege of Computer Sciences and Mathematics University of MosulThe Traffic signs are considered as Traffic Safety tools, Because of their role in the organization of traffic and vehicles to insure the safety of the passengers, pedestrians and the structures of traffic signs are very important devices which help the drivers to drive in safety and adequate manner. In this research Traffic sign detection  performed in two stages: The first stage include the traffic sign detection and extraction from the road image scene, depending on the color features of the sign, the red color  of the image was taken by using RGB color space system and applying threshold method, in which, for each layer specific threshold was applied. Considering the information of the external shape to recognize the shape geometry type of external frame by using Chain Code. While the second stage include traffic sign classification depending on inner contents of the sign, depending on the number of objects found in the inside part of the sign. Then, the Chain Code was used to recognize the boundary of the inner content of the sign. The research applied on a group of images with (.bmp, .jpg) extensions and with various sizes. The distinction percentage was (99%), the database included 30 images; 15 of them are warning and the other 15 are regulatory.https://csmj.mosuljournals.com/article_163722_5b3b06a16db0487b0b80f5437625a3d6.pdfimage processingobject recognitionchain codetraffic signred color recognition. color detection
collection DOAJ
language Arabic
format Article
sources DOAJ
author Sundus Ebraheem
Reham Al-Atiwi
spellingShingle Sundus Ebraheem
Reham Al-Atiwi
Traffic sign recognition by using chain code
Al-Rafidain Journal of Computer Sciences and Mathematics
image processing
object recognition
chain code
traffic sign
red color recognition. color detection
author_facet Sundus Ebraheem
Reham Al-Atiwi
author_sort Sundus Ebraheem
title Traffic sign recognition by using chain code
title_short Traffic sign recognition by using chain code
title_full Traffic sign recognition by using chain code
title_fullStr Traffic sign recognition by using chain code
title_full_unstemmed Traffic sign recognition by using chain code
title_sort traffic sign recognition by using chain code
publisher Mosul University
series Al-Rafidain Journal of Computer Sciences and Mathematics
issn 1815-4816
2311-7990
publishDate 2012-12-01
description The Traffic signs are considered as Traffic Safety tools, Because of their role in the organization of traffic and vehicles to insure the safety of the passengers, pedestrians and the structures of traffic signs are very important devices which help the drivers to drive in safety and adequate manner. In this research Traffic sign detection  performed in two stages: The first stage include the traffic sign detection and extraction from the road image scene, depending on the color features of the sign, the red color  of the image was taken by using RGB color space system and applying threshold method, in which, for each layer specific threshold was applied. Considering the information of the external shape to recognize the shape geometry type of external frame by using Chain Code. While the second stage include traffic sign classification depending on inner contents of the sign, depending on the number of objects found in the inside part of the sign. Then, the Chain Code was used to recognize the boundary of the inner content of the sign. The research applied on a group of images with (.bmp, .jpg) extensions and with various sizes. The distinction percentage was (99%), the database included 30 images; 15 of them are warning and the other 15 are regulatory.
topic image processing
object recognition
chain code
traffic sign
red color recognition. color detection
url https://csmj.mosuljournals.com/article_163722_5b3b06a16db0487b0b80f5437625a3d6.pdf
work_keys_str_mv AT sundusebraheem trafficsignrecognitionbyusingchaincode
AT rehamalatiwi trafficsignrecognitionbyusingchaincode
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