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Network Intrusion Detection System Using Ensemble of Binary Deep Learning Classifiers Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Feature Extraction Using DCT Based Traffic Sign Recognition

Authors : Surbhi Jha, Ajay Khunteta

Published in: Smart Trends in Information Technology and Computer Communications

Publisher: Springer Singapore

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Abstract

Traffic sign recognition (TSR) is a complex system to recognize many traffic sign, but sometimes it does not gives the correct result. To solve the problem of this system introduced self-organization Feature map (SOFM) neural network to classify traffic sign and feature extracted by Discrete Cosine Transform (DCT) of sign images. The proposed scheme is tested under manual database and shows the effectiveness by recognition rate is high and extraction time is less as compared to literature works.

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previous chapter Challenges in the Field of Aspect Level Sentiment Analysis
next chapter Exploring Cooperative Multi-agent Reinforcement Learning Algorithm (CMRLA) for Intelligent Traffic Signal Control
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Metadata
Title
Feature Extraction Using DCT Based Traffic Sign Recognition
Authors
Surbhi Jha
Ajay Khunteta
Copyright Year
2018
Publisher
Springer Singapore
Book
Smart Trends in Information Technology and Computer Communications

Print ISBN: 978-981-13-1422-3

Electronic ISBN: 978-981-13-1423-0

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-981-13-1423-0_8

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