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So the task at hand is to detect the denomination of any currency banknote. The dataset I have is about 2k images of each denomination (12 in total). An example banknote (after noise removal, erosion , dilation etc) looks like this:

enter image description here

enter image description here

Is it possible to somehow fine-tune a digit-detection (in the wild) model (such as those trained using the SHVN dataset) to make it a multi-digit detector? Or is it preferred to simply use a multi-digit detector as the base model and train it (transfer learning?) using my banknotes dataset?

I also wanted some ideas on localizing the position of the number on the banknote, as then the detection using CNN would be more reliable, if I feed it the cropped out image which just contains the number. I tried using pyTesseract for this, but even after tinkering with the settings, it did not give satisfactory results. Are there any other methods that can be used for this kind of localization?

Thank you in advance.

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