Abstract
Nowadays great concern for everyone is health; hence primary requirement for sound health is eating good quality fruits. However, most of the available fruits in the market are ripened using hazardous chemicals such as calcium carbide, which is highly hazardous to human health. In the existing literature, less focus is given towards addressing the problem of identification of artificially as well as naturally ripened fruits, due to the complex nature of problem. In order to solve this problem, a new framework is proposed in this paper, which utilizes both the image features- and sensor-based techniques to identify whether the fruit is ripened by chemicals or not. By employing pH-sensor based techniques and visual features, it is possible to detect artificially ripened fruits and save the human beings from serious health hazards. The experiments were conducted and the results indicate that the proposed technique is performing better for the identification of artificially ripened banana fruits.
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Meghana, N.R., Roopalakshmi, R., Nischitha, T.E., Kumar, P. (2019). Detection of Chemically Ripened Fruits Based on Visual Features and Non-destructive Sensor Techniques. In: Pandian, D., Fernando, X., Baig, Z., Shi, F. (eds) Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB). ISMAC 2018. Lecture Notes in Computational Vision and Biomechanics, vol 30. Springer, Cham. https://doi.org/10.1007/978-3-030-00665-5_84
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DOI: https://doi.org/10.1007/978-3-030-00665-5_84
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