000			02102nam a2200265 a 4500
001			vtls000054756
003			KUKTEM
005			20251114204457.0
008			110714t2010 my a f m 000 0 eng d
020			_aTHE0005970(Local)
039		9	_a201905141620 _baida _c201107181433 _dida _y201107141336 _zida
040			_aUMP
090			_aTA1637 .K43 2010 rs Bc.
100	0		_aKhairun Nor Aimi Ghazali
245	1	0	_aPalm oil classification using RGB and fuzzy / _cKhairun Nor Aimi Ghazali
246	3		_aPalm oil classification using RGB and fuzzy _h[computer file]
260			_aKuantan, Pahang : _bUMP, _c2010
300			_axiv, 84 p. : _bill. (some col.) ; _c30 cm. + _e1 computer disc
502			_aProject paper (Bachelor of Electrical Engineering (Electronics)) -- Universiti Malaysia Pahang - 2010
504			_aBibliography : p. 70-72
520	3		_aThis research is about to classification palm oil by using RGB and Fuzzy. As we know the current practice in the oil palm is to grade the oil palm bunches manually using human graders for separate which one for producing oil or others effectiveness. This method is subjective and subject to disputes. In this case, we developed systems by using image processing technique RGB as a preprocessing and fuzzy logic as classifier. The RGB color technique is utilized as the extracted features for the oil palm fruit rind. Further, the extracted feature is classified using fuzzy logic system to determine the ripeness level of the oil palm fruit. The system has been design to act like human eye and brain by process the fruit images and made a decision based on selected category. The result shows that it was successful discriminate the fruit bunches with accuracy False Rejection Rate (FRR) about 10% and False Acceptance Rate 0% for ripe categories, 20% and 0% False Rejection Rate (FRR) and 0% for False Acceptance Rate (FAR) for under ripe and unripe categories.
650		0	_aImage processing _xDigital technique
650		0	_aFuzzy logic
999			_aVIRTUA40 _c2701 _d2707
999			_aVTLSSORT0080*0200*0400*0900*1000*2450*2460*2600*3000*5020*5040*5200*6500*6501*9992