29 August 2016 Credit card account numbers detection and extraction from camera-based images
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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.
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Yunyun Yang, Yunyun Yang, Youbin Chen, 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); doi: 10.1117/12.2245104; https://doi.org/10.1117/12.2245104
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