MARC View

000			03019nam a2200265 a 4500
001			vtls000054715
003			KUKTEM
005			20251114204449.0
008			110712t2010 my a f m 000 0 eng d
020			_aTHE0007054(Local)
039		9	_a201906131017 _bhanafiah _c201107140059 _dVLOAD _y201107121415 _zida
040			_aUMP
090			_aTK7882.B56 Z37 2010 rs Bc.
100	0		_aNurul Zarina Md Isa
245	1	0	_aGender recognition based on facial image extraction / _cNurul Zarina Md Isa
246	3		_aGender recognition based on facial image extraction _h[computer file]
260			_aKuantan, Pahang : _bUMP, _c2010
300			_axvi, 66 p. : _bill. (some col.) ; _c30 cm. + _e1 computer disc
502			_aProject paper (Bachelor of Electrical Engineering (Electronics)) -- Universiti Malaysia Pahang - 2010
504			_aIncludes bibliographical references
520	3		_aIn principle, to combine face detection and gender classification methods may seem simple. However, this process is more complex than it appears because requires many aspects for consideration. The gender classification has attracted much attention in psychological literature, relatively few machine vision methods have been proposed. However it has been extensively studied in the context of surveillance applications and biometrics. This project is mainly concern with offline gender classification using purely image processing technique which using a database that was included in the system. The way of doing this is by extracting the differences between male and female facial features. Obviously the classification base on a single feature is not adequate since humans share many facial properties even within different gender group. So multilayer processing is needed. This project is working as expected based on the scope and objective of project. Although not many varieties of facial images have been considered like colored hair the basic techniques should be just the same. For the system classification, Template Matching Technique is used to match image with the database image. The system attempts are made to capture the most appropriate representation of face images as a whole and exploit the statistical regularities of pixel intensity variations. When attempting recognition, the unclassified image is compared with all the database images, returning a vector of matching score. The unknown person is then classified as the one giving the highest cumulative score. This project will be build using the MATLAB software. Overall, the project can be used and developed for various purposes, particularly to expedite the process of searching the database. The refinement of this project in other hand can lead to more accurate and reliable result by considering other facial properties like eyes, nose and eyebrows
650		0	_aBiometric identification
650		0	_aHuman face recognition (Computer science)
999			_aVIRTUA40 _c2489 _d2495
999			_aVTLSSORT008002000400090010002450246026003000502050405200650065019992