Abstract
Most of the time the people are finding it difficult to recognize the paper currencies due to their inability to see. Also in real life, it is not possible to trust the people to help a visual impaired person in recognizing the paper currency. But, in this regard, we can always trust an application that is easy to access and trust worthy. For building the application for the same, we need the help of machine learning algorithms. Several algorithms of machine learning such as supervised, unsupervised, semi-supervised, and reinforcement learning are available. Our paper mainly focuses on the recognition of different currency notes for the visually impaired people by using machine learning and taking the model as ResNet50 which is a 50 layers deep convolutional neural network. We have also used image processing by resizing and crop** the image to extract the important features of the notes so that the machine can recognize the currency notes efficiently. Our main contribution in this paper is through using various methods of image processing and feeding those processed image in our model, so that this model gets a fairly high accuracy.
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Maity, A., Roy, S.G., Bhattacharjee, S., Dutta, P., Singh, J. (2023). Prediction of Indian Currency for Visually Impaired People Using Machine Learning. In: Asari, V.K., Singh, V., Rajasekaran, R., Patel, R.B. (eds) Computational Methods and Data Engineering. Lecture Notes on Data Engineering and Communications Technologies, vol 139. Springer, Singapore. https://doi.org/10.1007/978-981-19-3015-7_19
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DOI: https://doi.org/10.1007/978-981-19-3015-7_19
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