Palm oil classification using RGB and fuzzy / (Record no. 2701)

MARC details
000 -LEADER
fixed length control field 02102nam a2200265 a 4500
001 - CONTROL NUMBER
control field vtls000054756
003 - CONTROL NUMBER IDENTIFIER
control field KUKTEM
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251114204457.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 110714t2010 my a f m 000 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number THE0005970(Local)
039 #9 - LEVEL OF BIBLIOGRAPHIC CONTROL AND CODING DETAIL [OBSOLETE]
Level of rules in bibliographic description 201905141620
Level of effort used to assign nonsubject heading access points aida
Level of effort used to assign subject headings 201107181433
Level of effort used to assign classification ida
-- 201107141336
-- ida
040 ## - CATALOGING SOURCE
Original cataloging agency UMP
090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN)
Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) TA1637 .K43 2010 rs Bc.
100 0# - MAIN ENTRY--PERSONAL NAME
Personal name Khairun Nor Aimi Ghazali
245 10 - TITLE STATEMENT
Title Palm oil classification using RGB and fuzzy /
Statement of responsibility, etc. Khairun Nor Aimi Ghazali
246 3# - VARYING FORM OF TITLE
Title proper/short title Palm oil classification using RGB and fuzzy
Medium [computer file]
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Kuantan, Pahang :
Name of publisher, distributor, etc. UMP,
Date of publication, distribution, etc. 2010
300 ## - PHYSICAL DESCRIPTION
Extent xiv, 84 p. :
Other physical details ill. (some col.) ;
Dimensions 30 cm. +
Accompanying material 1 computer disc
502 ## - DISSERTATION NOTE
Dissertation note Project paper (Bachelor of Electrical Engineering (Electronics)) -- Universiti Malaysia Pahang - 2010
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Bibliography : p. 70-72
520 3# - SUMMARY, ETC.
Summary, etc. This 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 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Image processing
General subdivision Digital technique
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Fuzzy logic
Holdings
Withdrawn status Lost status Damaged status Not for loan Home library Current library Date acquired Total checkouts Full call number Barcode Date last seen Copy number Price effective from Koha item type
  Not lost   Not for loan UMPLIB PEKAN UMPLIB PEKAN 04/09/2019   TA1637 .K43 2010 rs Bc. 0000058416 04/09/2019 1 04/09/2019 Final Year Report
  Not lost   Not for loan UMPLIB PEKAN UMPLIB PEKAN 04/09/2019   CD 5384 | TA1637 .K43 2010 rs Bc. 0000058417 04/09/2019 1 04/09/2019 Final Year Report

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