Credit card account numbers detection and extraction from camera-based images

Yunyun Yang; Youbin Chen

doi:10.1117/12.2245104

29 August 2016 Credit card account numbers detection and extraction from camera-based images

Yunyun Yang, Youbin Chen

Proceedings Volume 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016); 100332X (2016) https://doi.org/10.1117/12.2245104
Event: Eighth International Conference on Digital Image Processing (ICDIP 2016), 2016, Chengu, China

Abstract

Credit card account number detection and extraction from camera-based images is of vital importance in automatically inputting system of mobile devices. In this paper, we propose a novel framework to detect and extract credit card account number from camera-based images. Firstly radon transformation is used to detect and correct the degree of skew of the credit card, Secondly a morphological binary map is generated by calculating difference between the closing image and the opening image. Then horizontal projection and k-means are applied to get the card-number lines. Candidate regions are connected by using a morphological dilation operation. Last text lines are refined using a sliding window and an SVM classifier trained on two local texture distribution features: HOG and an improved local region binary pattern (LRBP). Experiences show the proposed method is robust to different contrast and complex environment.

Citation Download Citation

Yunyun Yang and Youbin Chen "Credit card account numbers detection and extraction from camera-based images", Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 100332X (29 August 2016); https://doi.org/10.1117/12.2245104

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KEYWORDS

Binary data

Cameras

Databases

Target detection

Mobile devices

Image fusion

Radon transform

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