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Real time face detection system / Amy Safrina Mohd Ali

By:

Amy Safrina Mohd Ali

Material type: Text

TextPublication details: Kuantan, Pahang : UMP, 2009Description: 57 p. : ill. (some col.) ; 30 cm. + 1 computer discISBN:

THE0006672(Local)

Other title:

Real time face detection system [electronic resource]

Subject(s):

Dissertation note: Project paper (Bachelor of Electrical Engineering (Electronics)) -- Universiti Malaysia Pahang - 2009 Abstract: 䚐ÔﴈÔ face detection system is a computer application for automatically detecting a human face from digital image or video frame from a video source. This project is used web camera to capture the image in real time. This face detection system used Haar Classifier method to detect face and extract human face. Haar Classifier technique can detect human face very face and can achieve high detection accuracy. This system is build using Visual Studio C++ 8 edition and Opencv to setup the interface between web camera and computer. This system also used Graphical User Interface (GUI) to design client window. Besides that this system used Graphic Device Interface (GDI) library to select the interest region. This system can detect the face image and can automatically save the image. This system can be applied in the banking system to reduce the number of forgery.

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Holdings ( 2 )
Title notes ( 2 )

Holdings
Item type	Current library	Call number	Copy number	Status	Date due	Barcode
Final Year Report	UMPLIB PEKAN	TK788.2 B56 A49 2009 rs Bc. (Browse shelf(Opens below))	1	Not for loan		0000037854
Final Year Report	UMPLIB PEKAN	CD 3302 \| TK788.2 B56 A49 2009 rs Bc. (Browse shelf(Opens below))	1	Not for loan		0000037855

Project paper (Bachelor of Electrical Engineering (Electronics)) -- Universiti Malaysia Pahang - 2009

䚐ÔﴈÔ face detection system is a computer application for automatically detecting a human face from digital image or video frame from a video source. This project is used web camera to capture the image in real time. This face detection system used Haar Classifier method to detect face and extract human face. Haar Classifier technique can detect human face very face and can achieve high detection accuracy. This system is build using Visual Studio C++ 8 edition and Opencv to setup the interface between web camera and computer. This system also used Graphical User Interface (GUI) to design client window. Besides that this system used Graphic Device Interface (GDI) library to select the interest region. This system can detect the face image and can automatically save the image. This system can be applied in the banking system to reduce the number of forgery.