• Parkavi K
• Rasathi K
• Sengeni K
• Abinaya P

Fruits are normally require them to be manually identified. This paper aims to find a best way of fruit classification method. This can be done by using supervised machine learning algorithms and image processing mechanism. It based on multi-feature extraction methods. Initially we preprocess the sample of fruit. It separating foreground and background using preprocessing method. The Scaling and cropping can be performed to reduce the image dimension. So that the processing is fast. Then we extract features from the fruit image and we also check the quality of fruits. Extracted features are fitted into the AdaBoost classifier machine learning algorithm. The obtained result will gives us the prediction accuracy. This result have been collected using a fruit image database . It consist of 5 different classes of fruits and 120 fruits image overall. Therefore average prediction accuracy of more than 85%.

Fruits, machine learning,svm algorithm

"Fruits classification using machine learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 3, page no.1256-1260, March-2021, Available :http://www.jetir.org/papers/JETIR2103173.pdf

"Fruits classification using machine learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 3, page no. pp1256-1260, March-2021, Available at : http://www.jetir.org/papers/JETIR2103173.pdf