000			01916nam a2200265 a 4500
999			_c1233 _d1239
001			vtls000040252
003			KUKTEM
005			20251114204405.0
008			090714t2009 my a f m 000 0 eng|d
020			_aTHE0006672(Local)
039		9	_a201905171132 _bamirul _c201107132152 _dVLOAD _c200911091644 _dkam _c200908141647 _dVLOAD
040			_aUMP _cUMP
090			_aTK788.2 B56 A49 2009 rs Bc.
100	0		_aAmy Safrina Mohd Ali
245	1	0	_aReal time face detection system / _cAmy Safrina Mohd Ali
246	3		_aReal time face detection system _h[electronic resource]
260			_aKuantan, Pahang : _bUMP, _c2009
300			_a57 p. : _bill. (some col.) ; _c30 cm. + _e1 computer disc
502			_aProject paper (Bachelor of Electrical Engineering (Electronics)) -- Universiti Malaysia Pahang - 2009
520	3		_a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.
650		0	_aHuman face recognition (Computer science)
650		0	_aImage processing
650		0	_aBiometric identification
942			_2lcc _cTHESIS