Fruits Classification Using Image Processing Techniques - Chithra, PL; Henila, M (International Journal of Computer Sciences and Engineering, 2025)
A new method for classifying fruits using image processing technique is proposed in this paper. The data set used had 70 apple images and 70 banana images for training and 25 images of apple and 25 images of bananas for testing. RGB image was first converted to HSI image. Then by using Otsu’s thresholding method region of interest was segmented by taking into account only the HUE component image of the HSI image. Later, after background subtraction, a total of 36 statistical and texture features were extracted with the help of the coefficients obtained by applying wavelet transformation on the segmented image using Haar filter. Extracted features were given as inputs to a SVM classifier to classify the test images as apples and bananas. As KNN classification method did not give 100% accuracy while classification SVM classification method was used. 140 sample images of apples and bananas were used for training and 25 images of banana and 25 images of apples were used for testing the proposed algorithm. The proposed algorithm gave 100% accuracy rate.