Performance Comparison between PCA and ANN Techniques for Road Signs Recognition

Mohd Ali, Nursabillilah (2013) Performance Comparison between PCA and ANN Techniques for Road Signs Recognition. Applied Mechanics and Materials. pp. 611-616. ISSN 1660-9366

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Abstract

This study reports about a comparison in recognizing road signs between Neural Network and Principal Component Analysis (PCA). The road sign with circular, triangular, octagonal and diamond shapes have been used in this study. Two recognition systems to determine the classes of the road signs class were implemented which are based on Feed Forward Neural Network and Principal Component Analysis (PCA). The performance of the trained classifier using Scaled Conjugate Gradient (SCG) back propagation function in Neural Network and PCA technique were evaluated on our test datasets. The experiments show that the system using PCA has a higher accuracy as compared to Neural Network with a minimum of 94% classification rate of road signs.

Item Type:	Article
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:	Faculty of Electrical Engineering > Department of Mechatronics Engineering
Depositing User:	NURSABILLILAH MOHD ALI
Date Deposited:	31 Jul 2013 08:50
Last Modified:	28 May 2015 04:00
URI:	http://eprints.utem.edu.my/id/eprint/9021
Statistic Details:	View Download Statistic

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