Method of recognizing magnetic ink characters in ATM

A method of recognizing magnetic ink characters, and the method comprising:

• obtaining character-based waveforms of magnetic ink characters on a check by a magnetoresistive (MR) sensor of an automated teller machine that handles bills and checks;
• obtaining a waveform group corresponding to each of the magnetic ink characters from a plurality of waveforms by executing a waveform authentication algorithm on a microprocessor of the automated teller machine to determine a waveform group to which each of the character-based waveforms corresponds according to a preset authentication reference for the waveform groups, based on each of the character-based waveforms acquired by recognizing the magnetic ink characters with the MR sensor, wherein the preset authentication reference for the waveform groups is derived through reiterative deep learning of character-based waveform data of the MR sensor that are acquired on a per-character basis from legitimate checks on each of which magnetic ink characters are properly printed, the reiterative deep learning using Convolution Neural Network (CNN);
• obtaining an image of the check by a contact image sensor of the automated teller machine;
• performing optical character recognition (OCR) on the obtained image by the microprocessor of the automated teller machine to obtain results of the OCR;
• and
• comparing, for verification, the results of the OCR and waveform groups of the magnetic ink characters.