Open AccessClassification of Watermelon using Sound Processing.
Author(s) -
T Pavadharini,
Anita Hb
Publication year - 2020
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.d8498.049420
Subject(s) - naive bayes classifier , grading (engineering) , sound (geography) , random forest , computer science , artificial intelligence , machine learning , pattern recognition (psychology) , support vector machine , biology , acoustics , ecology , physics
In a country like India, wide variety of fruits are available. Fruits plays an important role in the health of human beings and naturally health improves, if the quality of the fruit is good. Grading of the watermelon quality helps the consumers and vendors. The proposed work is to classify the watermelons based on the sound. Sound file dataset is created manually by tapping the watermelon and recording the sound. Dataset consist of different types of watermelon. For this, different size, colour and shape of the watermelons are used. Features are extracted from the sound files. Naïve Bayes, SMO and Random Tree classifiers are used for classification. The proposed work has achieved average accuracy of 78.8 %.