Automatic Identification and Classifications for Fruits Using k-NN

Most fruit recognition techniques combine different analysis method like color-based, shaped-based, size-based and texture-based. This work classifies the fruits features based on the color RBG values and texture values of the first statistical order and second statistical of the Gray Level Co-occurrence Matrix (GLCM). It applies different classifies Fine K-NN, Medium K-NN, Coarse K-NN, Cosine K-NN, Cubic K-NN, Weighted K-NN. The accuracy of each classifier is 96.3%, 93.8%, 25%, 83.8%, 90%, and 95% respectively. The system is evaluated with 46 images by amateur photographers of seasonal fruits at the time namely, strawberry, apply and banana. 100% of these pictures were recognised correctly.