On the Use of Computer Vision for Numismatic Research

This paper examines the application of a deep learning approach to automatic coin recognition, via a mobile device and client-server architecture. We show that a convolutional neural network is effective for coin identification. During the training phase, we determine the optimum size of the training dataset necessary to achieve high classification accuracy with low variance. In addition, we propose a client-server architecture that enables a user to identify coins by photographing it with a smartphone. The image provided by the user is matched with the neural network on a remote server. A high correlation suggests that the image is a match. The application is a first step towards the automatic identification of coins and may help coin experts in their study of coins and reduce the associated expense of numismatic applications

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On the Use of Computer Vision for Numismatic Research

Cited by 2 publications

References 19 publications

Performance Analysis of Coin Matching Using Local Texture Features

Performance Analysis of Coin Matching Using Local Texture Features

Implementation of a Coin Recognition System for Mobile Devices with Deep Learning

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