DIMENSION AND COLOR CLASSIFICATION OF OLIVE FRUIT WITH IMAGE PROCESSING TECHNIQUES

DIMENSION AND COLOR CLASSIFICATION OF OLIVE FRUIT WITH IMAGE PROCESSING TECHNIQUES Abstract The development of image processing technology appears in agriculture as well as in many other fields. Various classifications are carried out for fruits and vegetables. These are processes such as determining the harvest time according to their degree of maturity, deciding the way of collection and performing packaging operations according to their dimension. This study aims to classify the fruit according to its intended use in order to benefit more from the olive fruit that is important in industrial terms. In this study, olive fruit is classified as big, medium, and small according to its dimensions. Also classified as black and green according to their colors. This classification process was made in MATLAB environment and the KNN algorithm and decision trees was used. The results are obtained with Euclid and Manhattan methods used with the KNN algorithm and are given comparatively. According to the application results, 100% success was achieved in both methods in color classification. In dimension classification, 89.2% classification success was achieved in KNN algorithm and 86.7% in decision tree method. Keywords : Image processing, olive classification, KNN classification algorithm, decision tree.