A Research on Bank Card Number Recognition Based on ASFF+YOLOv7 and Multi-Scale Feature Line Fusion

Electronic payments have become the primary mode of payment today, and bank card recognition is widely used in industries such as mobile, mobile banking, and third-party payments. To address issues such as low fault tolerance due to factors such as complex backgrounds, significant perspective distortion that is difficult to recover, and high illumination variation, we propose a Bank Card Number Recognition algorithm based on ASFF + YOLOv7 and Multi-Scale Feature Line Fusion. The algorithm comprises two parts: the front-end dataset generation stage introduces an efficient semi-automatic traditional bank card dataset generation algorithm, which reduces the manual annotation cost while ensuring relative accuracy and significantly improves work efficiency. In the back-end recognition stage, we have improved the traditional deep learning model for the long-tail digit string dataset, achieving a precision of 99.19% and a recall rate of 98.65%.