KADİR SABANCI, MURAT KÖKLÜ, MUHAMMED FAHRİ ÜNLERŞEN

Classification of Siirt and Long Type Pistachios (Pistacia vera L.) by Artificial Neural Networks

Quality is one of the important factors in agricultural products marketing. Grading machines have great role in quality control systems. The most efficient method used in grading machines today is image processing. This study aims to do the grading of high valued agricultural product of our land called pistachio that has two different types namely Siirt and Long type of pistachios by image processing methods and artificial neural networks. Photos of Siirt and long type of pistachios are taken by a Webcam with CCD sensor. These photos were converted to gray scale in Matlab. Afterwards, these photos were converted to binary photo format using Otsus Method. Then this data was used to train multi-layered neural network to complete grading. Matlab was used for both image processing and artificial neural networks. Successes of the grading with image processing and artificial neural networks for mixed type pistachios Siirt and Long were researched.

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