Shape Features based Apple and Banana Fruit Image Classification


Manjunath Ravikumar
Department of Computer Science Sri. Shivalingeshwar Governement First Grade Degree College Madanhipparga, Tq.Aland, Dist. Kalaburagi, Karnataka, India.
Department of Computer Science Sharanabasaveshwar College of Science, Kalaburagi, Karnataka, India.
Raghavendra Anantayya
Department of Computer Science Gulbarga University, Kalaburagi, Karnataka, India.


This paper presents the classification of Apple and Banana fruits by using images. Detection of fruits is a challenging task. Choosing the desired fruits from many other fruits task is cumbersome, so to eliminate this difficulty this experiment is carried out. This system works in three stages first image preprocessing, second, extraction of relevant features and at last classification. The fruit-360 dataset has taken for the images of fruits. The shape features are extracted from the input images of Apple and Banana. Finally, the extracted features were supplied as input to the most five popular classifiers; LDA, Naïve Bays, Logistic regression, SVM and KNN. The KNN classifier has given highest as 99.10% classification accuracy among other classifiers.