01916nam a2200265 a 4500 0 0 lcc 0 1 20000 20000 2019-09-04 0 TK788.2 B56 A49 2009 rs Bc. 0000037854 2019-09-04 00:00:00 1 2019-09-04 PSM 0 0 lcc 0 1 20000 20000 2019-09-04 0 CD 3302 | TK788.2 B56 A49 2009 rs Bc. 0000037855 2019-09-04 00:00:00 1 2019-09-04 PSM 1233 1239 vtls000040252 KUKTEM 20251114204405.0 090714t2009 my a f m 000 0 eng|d THE0006672(Local) 201905171132 amirul 201107132152 VLOAD 200911091644 kam 200908141647 VLOAD UMP UMP TK788.2 B56 A49 2009 rs Bc. Amy Safrina Mohd Ali Real time face detection system / Amy Safrina Mohd Ali Real time face detection system [electronic resource] Kuantan, Pahang : UMP, 2009 57 p. : ill. (some col.) ; 30 cm. + 1 computer disc 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. Human face recognition (Computer science) Image processing Biometric identification lcc THESIS