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- W3178826352 abstract "Bruising on apples is mainly caused due to mechanical damage during harvesting and postharvest journey to the supermarket. Apple's bruise damage reduces the quality of apple as well as market price. This paper proposes an ultrasonic signal analysis technique to classify bruised and unbruised apples. An ultrasound signal with 100 kHz center frequency has been applied on the apple surface and the response signal has been recorded in reflectance mode. Principal Component Analysis (PCA) has been applied to the acquired response signals to reduce the dimensionality of the dataset. The first fifteen PCA components that contain more than 99% information have been used as the working dataset for classification. Then, the Support Vector Machine (SVM) classifier has been applied to this reduced dataset to classify bruised apple. SVM is trained with the training dataset that consists of data from both bruised and unbruised apples. The model developed after SVM training, is used to classify the test dataset. The classification result shows promising accuracy in the tune of 98%. This ultrasonic technique can endow with a new paradigm for automatic non-destructive identification of bruise-damaged apples." @default.
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- W3178826352 date "2021-01-01" @default.
- W3178826352 modified "2023-09-25" @default.
- W3178826352 title "Classification of Bruised Apple Using Ultrasound Technology and SVM Classifier" @default.
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- W3178826352 doi "https://doi.org/10.1007/978-981-16-0878-0_56" @default.
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