000 02653nam a2200241 a 4500
001 vtls000067893
003 KUKTEM
005 20251114204529.0
008 121220t2012 my da f m 000 0 eng d
020 _aTHE0002952(Local)
039 9 _a201905140837
_bzul
_y201212201503
_zhuda
040 _aUMP
090 _aTA1637 .S33 2012 rs Bc.
100 0 _aSiti Nur Saadah Mohd Jali
245 1 0 _aBanana grading system using color histogram (BGS) /
_cSiti Nur Saadah Mohd Jali
260 _aKuantan, Pahang :
_bUMP,
_c2012
300 _ax, 68 p. :
_bill. (some col.) ;
_c30 cm. +
_e1 CD-ROM
502 _aProject paper (Bachelor of Computer Science (Graphics & Multimedia Technology)) -- Universiti Malaysia Pahang - 2012
504 _aBibliography : p. 57-58
520 3 _aBananas Grading System (BGS) which is one of the system using image processing technique. The purpose of BGS is used to standardize the grading of the banana and distinguish between three differences classes of banana which are unripe, ripe and overripe. This BGS used computer system to analyze and interprets images that correspondent to human eye and mind. This study is taken into account of four types of banana fruits which are ‘Pisang Lemak Manis’, ‘Pisang Mas’, ‘Pisang Putar’ and ‘Pisang Berangan’. It attempts to form the decision by analysing the skin colour and condition. Bananas Grading System (BGS) is been done manually which brings variation of the results for banana grading. Since the colour is one of the most significant criteria related to fruit identification and fruit quality, it is a good indicator for ripeness. Therefore, fruits grading in present study only considers the colour of the skin of the bananas. The method that is used to develop this BGS is image processing method in term of color histogram of RGB. The color histogram method is evaluating the mean value of red, green and blue in order to classify the banana. In this BGS, fifty sample of banana is tested. From the result, the successful rate of grading the banana is 85% percent while the error rate is 15% percent. , based on the objective of this system which is to develop grading system to judge the maturity level and to standardize the banana grading based on maturity level, the objective is successfully achieved the goal. The problem regarding grading system by using Human Visualization System also solved. The cost of manual grading system, the time for grading the bananas and the man power uses is decreased.
650 0 _aImage processing
_xDigital technique
999 _aVIRTUA40
_c3625
_d3631
999 _aVTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5040*5200*6500*9992