MARC View

000			02749nam a2200277 a 4500
001			vtls000054823
003			KUKTEM
005			20251114204505.0
008			110718t2010 my a f m 000 0 eng d
020			_aTHE0007059(Local)
039		9	_a201906131024 _bhanafiah _c201107181533 _dida _y201107181532 _zida
040			_aUMP
090			_aTK7882.P3 K43 2010 rs Bc.
100	0		_aKhairul Bariyah Abd Rahim
245	1	0	_aOnline fingerprint recognition / _cKhairul Bariyah Abd Rahim
246	3		_aPC based control smart home system using Zigbee wireless technology _h[computer file]
260			_aKuantan, Pahang : _bUMP, _c2010
300			_axv, 61 p. : _bill. (some col.) ; _c30 cm. + _e1 computer disc
502			_aProject paper (Bachelor of Electrical Engineering (Electronics)) -- Universiti Malaysia Pahang - 2010
504			_aBibliography : p. 51-54
520	3		_aFingerprints are the most popularly used in biometric identification and recognition systems, because they can be easily used and their features are highly reliable. Because of their uniqueness and consistency over time, fingerprint has been used for identification for over a century, more recently becoming automated due to advancements in computing capabilities. The systems are increasingly employed into business, trading and living fields for automatic personal identification. Besides that, fingerprint recognition beyond criminal identification applications to several civilian applications such as access control, time and attendance, and computer user login. This project introduces and implementation of an online fingerprint recognition system which is capable of verifying identities of people so fast, accurate and suitable for the real time. Such a system has great utility in a variety of personal identification and access control applications by operating in minutiae extraction and minutiae matching. Minutiae extraction algorithm is implemented for extracting features from an input fingerprint image captured with an online inkless scanner. For minutiae matching, the matching algorithm has been developed. This algorithm is capable of finding the correspondences between minutiae in the input image and store template. The system will be tested on set of fingerprint images captured with inkless scanner. The recognition accuracy is found to be acceptable. This result shows that our systems meet the response requirement of online recognition with high accuracy. All the systems will be built using MATLAB software
650		0	_aPattern recognition systems
650		0	_aFingerprints _xIdentification
650		0	_aBiometric identification
999			_aVIRTUA40 _c2931 _d2937
999			_aVTLSSORT008002000400090010002450246026003000502050405200650065016502*9992