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Fruit Categorization Technique by using Fuzzy Logic and Neural Network

Mohd Nordin, Siti Nooratiqah (2014) Fruit Categorization Technique by using Fuzzy Logic and Neural Network. IRC, Universiti Teknologi PETRONAS. (Unpublished)

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Before fruits can be issued to the consumers, the fruits will be going through thorough processes and one of the processes is grading. The fruits will be graded according to the standard. The standard is based on the fruits’ country of origin (Malaysian Standard, MS and FAMA Standard). This project is a Matlab simulation of fruits categorization (grading) using artificial intelligent (AI) technique (Fuzzy Logic and Artificial Neural Network) in order to overcome problems faced on the existing system or current method. It is also to ease, fasten the process of fruit grading, and produce consistent and accurate result. Since there are numerous types of fruits, this project will only be focusing on the grading of mangoes, papayas and starfruits or carambola. The input of the system will be the properties that needed to determine the grade of the fruits such as weight, color, shape and the exterior condition of the fruits (defect). Rather than using hardware such as scanner, camera to automatically detect or to give input to the system, the input of the system will be manually keyed in by user. The data of the input will be processed using Matlab Fuzzy logic (FL) and Neural Network (NN) toolbox. The system will process the input with the reference data programmed in the system. The output of the system will be the grade and size of the fruit.

Item Type: Final Year Project
Academic Subject : Academic Department - Electrical And Electronics - Pervasisve Systems - Digital Electronics - Design
Subject: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Engineering > Electrical and Electronic
Depositing User: Ahmad Suhairi Mohamed Lazim
Date Deposited: 24 Feb 2015 10:45
Last Modified: 25 Jan 2017 09:36
URI: http://utpedia.utp.edu.my/id/eprint/14754

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