Banana ripeness detection using image processing and fuzzy logic

Hadfi, Izzat Hafiz (2016) Banana ripeness detection using image processing and fuzzy logic. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

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Abstract

Nowadays, the agricultural industries had been expanding widely, and brings competition among the agricultural industry which will need them to have critical product quality management in order to surpass the competition. These agriculture industries includes the banana plantation industry which is the second most widely cultivated fruit in Malaysia. The current method to detect the ripeness of banana is using chemicals in order to obtain the characteristic of the fruit. This method will harm the fruit and also affects its quality. There are also methods which is non-destructive to the products which uses man power to identify the banana. This method is time consuming. It is also a big disadvantage to use human eye to compare the indistinct color range of the banana. Furthermore, it is a disadvantage for the customer to pick a banana with less knowledge of the fruit and without knowing any recommendations on the current fruit ripeness. Thus the objective of this project is to determine the correct method in assisting users in selecting bananas. This project is proposing a combination of two Artificial Intelligence techniques, namely Image Processing technique and Fuzzy Logic rules in a knowledge-based system for the solution. Several samples of un-ripe, ripe and over-ripe banana are taken to identify their red, green and blue (RGB) value. The RGB values are extracted by using MATLAB software. The values are then analyzed to create the membership functions for the fuzzy logic. Then a set of knowledge-based rules are implemented for the system to give recommendations to the user on the banana. Another sample of banana is also will be taken for testing. The testing goes through RGB extraction and the fuzzy logic will be used to identify the ripeness of the banana. From the result of the ripeness, the system will give recommendations on the fruit including suggested meal preparation and the best before date to consume the banana. This proposed system contributes to both farmers and customers. As for the farmer, they can pick their best product to be sold to the market. While for the customers, they can choose efficiently their desired banana ripeness by using this system.

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