Providing an automatic Sorting system with low error percentage to Golden delicious apple helping image processing and ANFIS

In order to prevent damage to the fruit during transportation and help to fruit marketing, the fruits have to place in suitable package. There are several methods for sorting by weight such as the indirect, the mechanical and electrical methods. If data of fruit that are gotten using image processing are analysed by the suitable method, the indirect method has higher accuracy than other methods and is less expensive. In this study, 100 samples of Golden delicious apples were randomly selected from an orchard in Kermanshah – Iran (longitude: 7.03ºE; latitude: 4.22ºN). The algorithm that was developed in MATLAB was able to measure Area, Eccentricity, Perimeter, Length/Area, B_ave, G_ave, R_ave, Wide, contrast, texture, Wide/Area, Wide/Length, roughness, Length. In ANFIS model, samples were divided into two sets, with 70% for training set and 30% for testing set. In the best model for ANFIS and linear regression R2, SSE, MSE were 0.995, 119.42, 6.28 and 0.884, 14532.7, 151.38 respectively. So it can be concluded that if the data analysis be done using ANFIS method, indirect sorting system can be launched with low error percentage.

Keywords:

Sorting system , Mass modelling , Golden delicious apple , ANFIS