Real time face detection system /
Amy Safrina Mohd Ali
Real time face detection system / Real time face detection system [electronic resource] Amy Safrina Mohd Ali - 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.
THE0006672(Local)
Human face recognition (Computer science)
Image processing
Biometric identification
Real time face detection system / Real time face detection system [electronic resource] Amy Safrina Mohd Ali - 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.
THE0006672(Local)
Human face recognition (Computer science)
Image processing
Biometric identification