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Face recognition using neural network / Alfatihah Abdullah

By:

Alfatihah Abdullah

Material type: Text

TextPublication details: Kuantan, Pahang : UMP, 2010Description: xiv, 62 p. : ill. (some col.) ; 30 cm. + 1 computer discISBN:

THE0007049(Local)

Other title:

Face recognition using neural network [computer file]

Subject(s):

Dissertation note: Project paper (Bachelor of Electrical Engineering (Electronics)) -- Universiti Malaysia Pahang - 2010 Abstract: Facial recognition systems are computer-based security systems that are able to automatically detect and identify human faces. Facial recognition has gained increasing interest in the recent decade. Over the years there have been several techniques being developed to achieve high success rate of accuracy in the identification and verification of individuals for authentication in security systems. This project experiments the concept of neural network for facial recognition that can differentiate and recognize face of image. This face recognition system begins with image pre-processing and then the output image is trained using Backpropagation algorithm. Backpropagation network learns by training the inputs, calculating the error between the real output and target output, and propagates back the error to the network to modify the weights until the desired output is obtained. After training the network, the recognition system is tested to ensure that the system can recognize the pattern of each face image. The purpose of this project is to recognize face of image for the recognition analysis using Neural Network. This project is mainly concern with offline facial recognition systems using purely image processing technique. The system will find database image has a maximum percentage on similarity of the pattern of the image. This project is also to design a pattern recognition system by applying Neural Network Toolbox in MATLAB software.

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Holdings ( 2 )
Title notes ( 3 )

Holdings
Item type	Current library	Call number	Copy number	Status	Date due	Barcode
Final Year Report	UMPLIB PEKAN	TK7882.B56 A44 2010 rs Bc. (Browse shelf(Opens below))	1	Not for loan		0000058484
Final Year Report	UMPLIB PEKAN	CD 5418 \| TK7882.B56 A44 2010 rs Bc. (Browse shelf(Opens below))	1	Not for loan		0000058485

Project paper (Bachelor of Electrical Engineering (Electronics)) -- Universiti Malaysia Pahang - 2010

Bibliography : p. 57-59

Facial recognition systems are computer-based security systems that are able to automatically detect and identify human faces. Facial recognition has gained increasing interest in the recent decade. Over the years there have been several techniques being developed to achieve high success rate of accuracy in the identification and verification of individuals for authentication in security systems. This project experiments the concept of neural network for facial recognition that can differentiate and recognize face of image. This face recognition system begins with image pre-processing and then the output image is trained using Backpropagation algorithm. Backpropagation network learns by training the inputs, calculating the error between the real output and target output, and propagates back the error to the network to modify the weights until the desired output is obtained. After training the network, the recognition system is tested to ensure that the system can recognize the pattern of each face image. The purpose of this project is to recognize face of image for the recognition analysis using Neural Network. This project is mainly concern with offline facial recognition systems using purely image processing technique. The system will find database image has a maximum percentage on similarity of the pattern of the image. This project is also to design a pattern recognition system by applying Neural Network Toolbox in MATLAB software.