A genetic algorithm and artificial neural network-based approach for the machine vision of plate segmentation and character recognition

College

Gokongwei College of Engineering

Department/Unit

Electronics And Communications Engg

Document Type

Conference Proceeding

Source Title

8th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management, HNICEM 2015

Publication Date

1-25-2016

Abstract

This paper proposes a genetic-algorithm and neural network-based approach in the optimization of the process of plate segmentation and character recognition respectively in intelligent transportation systems. Upon the detection of the vehicle's plate from a captured image, it is necessary that the individual characters in the detected plate are distinguished. After the process of plate recognition, the recognized plate number can be crossed-referenced against a database to correctly identify the vehicle's owner and ultimately penalize him for the traffic rule he violated. The segmentation algorithm captures the region of each character in the detected plate using genetic algorithm. After which, each plate character image is mapped against its corresponding sample character image. This is done by feeding sample character images into an artificial neural network and training the network. © 2015 IEEE.

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Digitial Object Identifier (DOI)

10.1109/HNICEM.2015.7393240

Disciplines

Electrical and Computer Engineering | Electrical and Electronics

Keywords

Pattern recognition systems; Intelligent transportation systems; Genetic algorithms; Computer vision

Shelf Location

Archives, The Learning Commons, 12F Henry Sy Sr. Hall

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