Optical character recognition has seen many applications in  machine learning and  deep learning. One such practical application of OCR is for identification of credit card type and number on the card. This could be of great help of banks and other financial institutions for digitally recognising the card numbers and type of card. It can also be useful for  UPI services where the user can just scan the card instead of typing in the details. OCR is usually handled by a library called  Tesseract. But, here we will use OpenCV to read the credit card and identify the type and number on the card.

The purpose of this article is to build a credit card reader with OpenCV and machine learning techniques to identify the card number and the card type. Let us get started.

Getting a Font Reference

On a typical credit card, you can see that the numbers are in a slightly different font. For these numbers to be read by the machine, we need to show the machine and save the font of these numbers. The font on the cards is called MICR which stands for magnetic ink character recognition code. So, let us now write the code in OpenCV and perform a template matching so that this font is understood for recognition later.

#opencv #python #credit card