Authors :
Raju D. Kamble; Sandip Rahane; Pranali Sakhare; V. G. Puranik
Volume/Issue :
Volume 10 - 2025, Issue 9 - September
Google Scholar :
https://tinyurl.com/3k4dpmuh
Scribd :
https://tinyurl.com/5n7vfk3t
DOI :
https://doi.org/10.38124/ijisrt/25sep1527
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
Traffic sign detection and recognition is an important part of the advanced driver assistance systems which can
alert drivers about traffic rules and regulations hence increase driver safety. In this article, challenges and undesirable
factors which affect performance of road traffic sign detection and recognition systems are discussed. The contributions of
recent works and different methodologies are described in this paper. In the proposed method region of interest are extracted
by using connected component and signs are successfully classified using Genetic Algorithm. The proposed method is
invariant of colour and shape of signs.
Keywords :
TSDR, ROI, RFA.
References :
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Traffic sign detection and recognition is an important part of the advanced driver assistance systems which can
alert drivers about traffic rules and regulations hence increase driver safety. In this article, challenges and undesirable
factors which affect performance of road traffic sign detection and recognition systems are discussed. The contributions of
recent works and different methodologies are described in this paper. In the proposed method region of interest are extracted
by using connected component and signs are successfully classified using Genetic Algorithm. The proposed method is
invariant of colour and shape of signs.
Keywords :
TSDR, ROI, RFA.