Classification of Watermelon using Sound Processing 
Pavadharini T1, Anita HB2
1Pavadharini T*., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India.
2Anita HB., Associate Professor, Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India.
Manuscript received on April 09, 2020. | Revised Manuscript received on April 21, 2020. | Manuscript published on April 30, 2020. | PP: 2489-2492 | Volume-9 Issue-4, April 2020. | Retrieval Number: D8498049420/2020©BEIESP | DOI: 10.35940/ijeat.D8498.049420
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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 %.
Keywords: Watermelon , Sound processing , Fast Fourier Transform (FFT), Naive Bayes, SMO, Random Tree.