TAN Shiyu,YANG Ling,SHI Chunxiang,et al.Bank Card Number Recognition System under the Complex Background based on Deep Learning[J].Journal of Chengdu University of Information Technology,2021,36(03):280-285.[doi:10.16836/j.cnki.jcuit.2021.03.007]
复杂背景下银行卡号识别方法研究
- Title:
- Bank Card Number Recognition System under the Complex Background based on Deep Learning
- 文章编号:
- 2096-1618(2021)03-0280-06
- Keywords:
- bank card number recognition; deep learning; OCR; neural network
- 分类号:
- TP391.41
- 文献标志码:
- A
- 摘要:
- 针对复杂背景下的银行卡号提取及识别问题提出一种基于深度学习和传统光学字符识别(optical character recognition,OCR)方法相结合的自动提取并识别卡号的算法。算法采用改进的深度学习文本检测模型对文本内容进行检测,然后利用OCR方法对数字部分图像进行分割,最后通过改进的神经网络识别数字得到连续的银行卡号。实验结果表明,改进了卷积核的神经网络对复杂背景下的银行卡号字符识别效果有显著提升,能较好提取图像中的字符特征信息,在浅色背景数据集下准确率可达到98.87%。该系统能有效识别复杂背景下的银行卡号,平均时效约为6.3 s。
- Abstract:
- Aiming at the problem of bank card number extraction and recognition in a complex background,this paper proposes an algorithm for automatic extraction and recognition of card numbers based on the combination of deep learning and traditional optical character recognition(OCR)methods.We use the algorithm of an improved deep learning text detection model to detect the text content,then we use the OCR method to segment the digital part of the image, and finally use an improved neural network to recognize the number to obtain a continuous bank card number.The experimental results show that the neural network with improved convolution kernel can significantly improve the character recognition of bank card numbers in complex backgrounds and can better extract the character feature information in the image,and the accuracy can reach 98.87% under the light background dataset. The system can effectively identify bank card numbers in complex backgrounds,and its average time limit is about 6.3 s.
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备注/Memo
收稿日期:2020-10-13
基金项目:四川省科技计划资助项目(2020YFH0122)