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Road Traffic Sign Recognition Based on Genetic Algorithm


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.

Paper Submission Last Date
31 - March - 2026

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