Machine Vision Using Cellphone Camera: A Comparison of deep networks for
  classifying three challenging denominations of Indian Coins
Keyur D. Joshi Dhruv Shah Varshil Shah Nilay Gandhi Sanket J. Shah Sanket B. Shah
Indian currency coins come in a variety of denominations. Off all the
varieties Rs.1, RS.2, and Rs.5 have similar diameters. Majority of the coin
styles in market circulation for denominations of Rs.1 and Rs.2 coins are
nearly the same except for numerals on its reverse side. If a coin is resting
on its obverse side, the correct denomination is not distinguishable by humans.
Therefore, it was hypothesized that a digital image of a coin resting on its
either size could be classified into its correct denomination by training a
deep neural network model. The digital images were generated by using cheap
cell phone cameras. To find the most suitable deep neural network architecture,
four were selected based on the preliminary analysis carried out for
comparison. The results confirm that two of the four deep neural network models
can classify the correct denomination from either side of a coin with an
accuracy of 97%.