000			01830nam a2200265 a 4500
999			_c11398 _d11404
001			vtls000018263
003			KUKTEM
005			20251117141112.0
008			070215t2004 my g t 001 0 may d
020			_aSC00000102(Local)
039		9	_a201905291436 _bnadia _c201107131902 _dVLOAD _c201105231428 _dFida _c200908141302 _dVLOAD
040			_aUMP _cUMP
090			_aTS1449 .Z34 2006 rs
100	0		_aZalili Musa
245	1	0	_aSistem pengesanan kerosakan pada jalinan tekstil / _cZalili binti Musa, Rohani Abu Bakar, Tuty Asmawaty Abdul Kadir
260			_aKuantan, Pahang : _bKUKTEM, _c2006
300			_axvii, 211 p. : _bill. ; _c30 cm.
500			_aResearch final report - vot RDU 05/1/17 (KUKTEM)
520			_aThe purpose of this study was to determine the best methodology, techniques, and algorithms in detecting defects on textile webs through several tests on the prototypes developed in the laboratory. Existing methodologies are based on statistical methods that emphasize on pixel density and relationship of grey level among neighboring pixels. This method, however, is not very effective in detecting defects on textile webs. From a series of tests conducted in this study, a methodology that was enhanced with a pre-processor module (Lili Methodology) was able to detect defects on all the five types of textile webs at 100% level. Four main modules used in this methodology were image acquisition, pre-processor, extraction, and texture analysis (see Figure 1). For each module, several enhanced techniques and algorithms that were based on existing techniques and algorithms were used to produce optimum results.
650		0	_aTextile fibers _xAnalysis _xComputer programs
650		0	_aTextile fibers _xTesting
700	0		_aRohani Abu Bakar
700	0		_aTuty Asmawaty Abdul Kadir
942			_2lcc _cSPECIAL