A Machine Learning and Computer Vision Application to Robustly Extract Winnings from Multiple Lottery Tickets in One Shot
Abstract
Mega Millions and Powerball are among the most popular American lottery games. This article provides a practical software application that can conveniently examine and evaluate several lottery tickets for prizes using just the images. The application accepts as input a directory containing the images of lottery tickets and utilizes machine learning and computer vision to extract lottery ticket data, lottery name, lottery draw date, 5-digit lottery numbers, 2-digit lottery "ball" numbers, and the lottery multiplier. The application also retrieves winning lottery data that corresponds to the lottery draw date using a public database API. This is compared with data collected from each lottery ticket image to establish matches, and the corresponding prize amount is computed. The current version of the application supports GPU usage, and image orientation has no impact on its functionality. It is believed that a considerable portion of the U.S. public participating in the Powerball and Mega Millions lotteries will find such an application beneficial and handy.
Downloads
Metrics
PlumX Statistics
References
2. Akenine-Moller, T. & Strom, J. (2008). Graphics Processing Units for Handhelds. Proceedings of the IEEE, 96(5), 779–789. https://doi.org/10.1109/JPROC.2008.917719
3. Allen-Zhu, Z. & Li, Y. (2019). What Can ResNet Learn Efficiently, Going Beyond Kernels? Advances in Neural Information Processing Systems, 32. https://proceedings.neurips.cc/paper/2019/hash/5857d68cd9280bc98d079fa912fd6740-Abstract.html
4. Awalgaonkar, N., Bartakke, P., & Chaugule, R. (2021). Automatic License Plate Recognition System Using SSD. 394–399. https://doi.org/10.1109/IRIA53009.2021.9588707
5. Bernadette McKinney, E. & Swain, J. W. (1993). State lotteries: Explaining their popularity. International Journal of Public Administration, 16(7), 1015–1033. https://doi.org/10.1080/01900699308524833
6. Castaño-Díez, D., Moser, D., Schoenegger, A., Pruggnaller, S., & Frangakis, A. S. (2008). Performance evaluation of image processing algorithms on the GPU. Journal of Structural Biology, 164(1), 153–160. https://doi.org/10.1016/j.jsb.2008.07.006
7. Google Cloud. (2022). Pricing Overview. https://cloud.google.com/pricing
8. JaidedAI (2022). EasyOCR (1.4.2) [Python]. https://github.com/JaidedAI/EasyOCR
9. Kemenade, H. Van, Murray, A., wiredfool, Jeffrey A. Clark, “Alex,” Karpinsky, A., Baranovič, O., Gohlke, C., Dufresne, J., DWesl, Schmidt, D., Kopachev, K., Houghton, A., Mani, S., Landey, S., Vashek, Ware, J., Piolie, Douglas, J., T, S., … Base, M. (2022). Python-Pillow (7.1.2). Zenodo. https://doi.org/10.5281/zenodo.6788304
10. Lucky for Life Lotteries (2022). Lucky for Life. https://www.luckyforlife.us/
11. Mega Millions (2022a). How to Claim a Mega Millions Prize. https://mega-millions.com/how-to-claim
12. Mega Millions (2022b). How To Play. https://www.megamillions.com/How-to-Play.aspx
13. Multi-State Lottery Association (2022). About. https://www.lottery.net/multi-state-numbers
14. O’Brien, S. (2021, March 15). A $1 million, year-old Mega Millions winning ticket expires March 17. Here’s how many prizes remain unclaimed. CNBC. https://www.cnbc.com/2021/03/15/mega-millions-ticket-worth-1-million-to-expire-join-unclaimed-prizes.html
15. Opencv (2022). Opencv (4.5.4) [C++]. OpenCV. https://github.com/opencv/opencv
16. Paszke, A., Gross, S., Massa, F., Lerer, A., Bradbury, J., Chanan, G., Killeen, T., Lin, Z., Gimelshein, N., Antiga, L., Desmaison, A., Kopf, A., Yang, E., DeVito, Z., Raison, M., Tejani, A., Chilamkurthy, S., Steiner, B., Fang, L., … Chintala, S. (2019). PyTorch: An Imperative Style, High-Performance Deep Learning Library. Advances in Neural Information Processing Systems, 32. https://papers.nips.cc/paper/2019/hash/bdbca288fee7f92f2bfa9f7012727740-Abstract.html
17. Pennsylvania Lottery (2022). Cash4Life. https://www.palottery.state.pa.us/Draw-Games/Cash4Life.aspx
18. Powerball (2022a). 9 ways to win! https://www.powerball.com/games/home
19. Powerball (2022b). How to Claim Powerball Winnings. https://www.powerball.net/how-to-claim-winnings
20. Prashanth, B., Mendu, M., & Thallapalli, R. (2021). Cloud based Machine learning with advanced predictive Analytics using Google Colaboratory. Materials Today: Proceedings. https://doi.org/10.1016/j.matpr.2021.01.800
21. Socrata (2022). Socrata Developers. https://dev.socrata.com/
22. Staudemeyer, R. C. & Morris, E. R. (2019). Understanding LSTM -- a tutorial into Long Short-Term Memory Recurrent Neural Networks (arXiv:1909.09586). arXiv. https://doi.org/10.48550/arXiv.1909.09586
23. The Lotter (2022). Top 6 Biggest Unclaimed Jackpots. https://www.thelotter.com/biggest-unclaimed-jackpots/
24. Tom Huddleston Jr (2022). The $1.28 billion Mega Millions jackpot would be one of the biggest ever—Here are the top 5 so far. CNBC. https://www.cnbc.com/2022/07/27/1-billion-mega-millions-jackpot-among-biggest-us-lottery-prizes.html
25. Van Rossum, G. & Drake, F. L. (2009). Python 3 Reference Manual. CreateSpace.
26. VikramjitSinghRathee (2022). A Machine Learning and Computer Vision Application to Compute Winnings from Multiple Lottery tickets (1.0) [Python]. https://github.com/VikramjitSinghRathee/A-Machine-Learning-and-Computer-Vision-Application-to-Compute-Winnings-from-Multiple-Lottery-tickets
27. Waller, P. (2022). Pyfiglet (0.8.post1) [Python]. https://github.com/pwaller/pyfiglet
28. xmunoz (2022). Sodapy (2.1.1) [Python]. https://github.com/xmunoz/sodapy
29. Xu, R., Han, F., & Ta, Q. (2018). Deep Learning at Scale on NVIDIA V100 Accelerators. 23–32. https://doi.org/10.1109/PMBS.2018.8641600
30. Ye, Q. & Doermann, D. (2015). Text Detection and Recognition in Imagery: A Survey. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37(7), 1480–1500. https://doi.org/10.1109/TPAMI.2014.2366765
Copyright (c) 2023 Wan Li, Vikramjit S. Rathee, Pengyue He
This work is licensed under a Creative Commons Attribution 4.0 International License.