Abstract:

Image processing methods are preferred by many researchers who want to produce innovative inventions with the change and development of technology. Especially in recent years, image processing methods have been used in almost every sector. The applications of image processing in the food and agricultural sectors are in these sectors and the studies continue increasingly. In this study, an application has been made to determine the type of olive fruit, which is one of the most important branches of agricultural activity. At the beginning of the study, the image of olive grains of known type was uploaded to the computer memory and analyzes were performed in the ‘R’ program, which is a statistical programming language. Numerical information of the olive grains in the image was obtained using the appropriate image processing techniques to optimize the image transferred to the system for analysis. This information was the numerical data in pixels that make up the size and color variables of the olive grains. The olive grains were analyzed using the K-Mean method and the Fuzzy C-Means algorithm with the help of the generated variables. Furthermore, as there was a preliminary information about the olive type, the success of the clustering that emerged as a result of the analysis in determining the types was evaluated in detail. As a result of the study, the cluster structure resulting from the analysis using the Fuzzy C-Means algorithm gave the closest results to the groups belonging to the olive grains whose type was actually known.

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