000			01984nmm a2200313 a 4500
001			vtls000098371
003			KUKTEM
005			20251117113325.0
008			161209s2016 my fq d 001 0 eng d
020			_aTHE0005064(Local)
039		9	_a201905101513 _bhanafiah _c201712191239 _dsaini _y201612091141 _zsaini
040			_aUMP
090			_aFKP .T365 2016 r Bc.
090			_aCD 10391
100	1		_aTan, Kai Yang
245	1	0	_aIntruder detection using histogram and edge detection algorithms _h[electronic resource] / _cTan Kai Yang
260			_aKuantan, Pahang : _bUMP, _c2016
300			_a1 computer disc : _bdigital data ; _c12 cm.
500			_aFaculty of Manufacturing Engineering
500			_aTheses Gred A
502			_aProject Paper (Bachelor of Mechatronics Engineering (Hons.)) -- Universiti Malaysia Pahang – 2016
520	3		_aNowadays, night vision technology enables a person to be seen in the dark. In the past, night vision was implemented by making use of the infrared spectrum of electromagnetic waves and devices such as image intensifiers. With the growing popularity of digital computing, many digital image processing techniques have been proposed to implement night vision. These techniques can enhance the images captured by ordinary cameras under low light conditions and can be implemented completely in software. The entire project is done by using image processing techniques via OpenCV which run on Linux environment. The challenge of this project focuses on the detection ability of intruder by using a webcam at a fixed position in low light condition.
538			_aItem in pdf format
610	2	0	_aFaculty of Manufacturing Engineering _xDissertations
650		0	_aUniversities and Colleges _xDissertations
650		0	_aTheses
856	4	0	_uhttp://ecollib.ump.edu.my/id/eprint/4001 _zAccess in library only
999			_aVIRTUA40 _c6736 _d6742
999			_aVTLSSORT0080*0200*0400*0900*0901*1000*2450*2600*3000*5000*5001*5020*5200*5380*6100*6500*6501*8560*9992