The task of recognizing the bank cards on images is considered in this paper. This task is motivated by premoderation of images in social networks in order to avoid leakage of personal data. An example of such data is the number of bank card. Detection algorithm based on convolutional neural networks is applied for this task. A number of experiments were conducted to develop the most optimal neural network architecture, which took into account the speed and accuracy of recognition. In the course of the experiments, the recognition accuracy of 91% and the processing speed of 25 images per second were achieved.
- M. A. Ali, B. Arief, M. Emms, A. van Moorsel. “Does the Online Card Payment Landscape Unwittingly Facilitate Fraud?” IEEE Security & Privacy, vol. 15, No. 2, pp.78 to 86, 2016.
- ArealIdea “Analysis of Computer Vision Algorithms” Webpage. https://arealidea.ru/articles/stati-i-publikatsii/analizalgoritmov-kompyuternogo-zreniya-poiska-obektov-isravneniya-izobrazheniy/ visited on 30.06.2018 (in Russian).
- I. O. Sakovich, Yu. S. Belov. “Survey on basic methods of contour analysis for highlighting the contours of moving objects” Engineering Journal: Science and Innovation, No. 12, 2014 URL: http://engjournal.ru/catalog/it/hidden/1280.html visited on 30.06.2018 (in Russian).
- P. Viola, M. Jones “Rapid object detection using a boosted cascade of simple features” Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.
- ImageNet Large Scale Visual Recognition Competition, http://www.image-net.org/challenges/LSVRC/2017/ visited on 30.06.2018.
- Y. LeCun, B. Boser, J. S. Denker, D. Henderson, R. E. Howard, W. Hubbard and L. D. Jackel: Backpropagation Applied to Handwritten Zip Code Recognition, Neural Computation, 1(4):541-551, Winter 1989.
- Tensor Flow: An open source machine learning framework for everyone, https://www.tensorflow.org/ visited on 30.06.2018.
- Cireşan D.C. “Deep big multilayer perceptrons for digit recognition” – Springer Berlin Heidelberg, 2012. – с. 581-589.