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基于 OpenCV 的银行卡号识别系统设计与实现

摘要通过输入银行卡号进行绑定是电子货币的互通的基础，但在越来越讲究效率的现在，如何

快速的输入卡号成为人们的关注点。因而，本设计设计了一个银行卡号识别系统，该系统完成了

银行卡号的识别。该系统是建立在 OpenCV 基础上的，对拍摄图片进行许多图像处理后得到银行卡

号位置，然后切割图片得到该区域，最后采用深度学习的识别模型对其识别，得到识别结果并进

行输出。通过多次识别结果对比，证明该系统具有较快的识别速度和较高的准确率，同时识别结

果相对稳定。

关键词银行卡卡号图像处理深度学习

Design and Implementation of Bank Card Number

Identification System Based on OpenCV

Abstract ： The identification of bank card numbers is the basis for the realization of

e-commerce and electronic money. Therefore, how to quickly and accurately identify bank card

numbers automatically becomes an important key technologyTherefore, this design designs a

bank card number identification system, the system completes the bank card number

identification. The system is built on the basis of OpenCV. After many image processing of the

pictures taken, the bank card number position is obtained, and then the image is cut to obtain

the region. Finally, the recognition model of deep learning is used to identify the image, and the

recognition result is obtained and output. Through the comparison of recognition results for

many times, it is proved that the system has fast recognition speed and high accuracy, and the

recognition results are relatively stable.

Key words bank card number Image processing deep learning

引言 .............................................................................................................................................................1

1 图像处理技术 .........................................................................................................................................2

1.1 图片整体提取...............................................................................................................................2

1.2 图像数据处理...............................................................................................................................3

1.2.1 灰度化...............................................................................................................................3

1.2.2 浮雕化...............................................................................................................................3

1.2.3 二值化...............................................................................................................................4

1.3 图像检测.......................................................................................................................................4

1.3.1 边缘检测...........................................................................................................................4

1.3.2 轮廓检测...........................................................................................................................5

1.3 图像截取.......................................................................................................................................6

2 基于深度学习的银行卡号自动识别算法 .............................................................................................7

2.1 深度学习.......................................................................................................................................7

2.2 模型结构.......................................................................................................................................7

2.3 具体模型.......................................................................................................................................8

2.3.1 CNN 模型...........................................................................................................................8

2.3.2 RNN 模型...........................................................................................................................9

3 实验结果与分析 ...................................................................................................................................12

3.1 数据集准备.................................................................................................................................12

3.2 实验过程.....................................................................................................................................12

3.3 实验结果与分析.........................................................................................................................13

4 结束语 ...................................................................................................................................................16

参考文献 ...................................................................................................................................................17

致谢 .......................................................................................................................................................18

附录 .......................................................................................................................................................19