Developing Software For Automated Palm Oil Fresh Fruit Bunch (FFB) Grading System, (AGS)

Nur-Iman, Mohammed Rosdi (2014) Developing Software For Automated Palm Oil Fresh Fruit Bunch (FFB) Grading System, (AGS). Project Report. UTeM, Melaka, Malaysia. (Submitted)

Text (24 Pages) Developing Software For Automated Palm Oil Fresh Fruit Bunch (FFB) Grading System (AGS) 24 Pages.pdf - Submitted Version Restricted to Registered users only Download (1MB)

Abstract

Sime Darby Plantation is the world's largest palm oil procedures, producing most of the world's crude palm oil output annually. With vast quantity of oil production annually, it is wise for the company to strive for better efficiency. One of the aspect that is worthwhile to exploit is the FFB quality assessment. In order to provide more accurate, reliable, consistent and quantitative infonnation in addition to the large volumes, image processing system is the solution to automate the grading process to replace the current grading of palm oil Fresh Fruit Bunches (FFB) that still perfonned manually through visual inspection based on the number empty socket present on the FFB. It is the intention here to introduce an automated FFB grading system using a Matlab based program called Automated Grading System (AGS) - Image Processing Unit which correlate the mesocarp color of fruit bunches to their corresponding ripeness and eventually sorts the fruit to five categories of ripeness. The methodology of this program can be divided to five main phases, i.e, image pre-processing, image morphological, colour space conversion and image segmentation. From the segmentation, Digital Numbers (DN) was obtained and fmally the image was classify according to their ripeness. The AGS- Image Processing Unit was able to classify the image received from AGS-Data Acquisition Unit to their respective classes. The unit also capable of analyzing the images with shorter time interval.

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