Applied aspects in informatics
Mathematical models of socio-economic processes
Dynamic systems
Scientometrics and management science
Recognition of images
N.S. Skoryukina Machine-readable zones localization method robust to capture conditions
N.S. Skoryukina Machine-readable zones localization method robust to capture conditions


This paper describes a method for machine-readable zones localization on document images captured using mobile digital cameras. The proposed method is based on feature points detection, filtration and clustering using Hough transform. The algorithm is designed in accordance of real-time requirements for running on mobile devices. Test results for real data are presented.


machine-readable zone, image analysis, mobile devices

PP. 81-86.


1. ICAO Doc 9303 Machine Readable Travel. Seventh Edition. Parts 2-7. 2015. International Civil Aviation Organization.
2. Bessmeltsev V.; Bulushev E., Goloshevsky N. Highspeed OCR algorithm for portable passport readers // Graphicon’ 11. 2011.  P. 25–29.
3. Visilter Y.V., Zheltov S.Y., and Lukin A.A., “Development of OCR system for portable passport and visa reader”. Proceedings  of SPIE, 1999, pp. 194-199.4.
4. Bulatov K.B., Polevoy D.V., Ilin D.A., Chernyshova Y.S. Problems of machine-readable zone recognition captured with digital  mobile cameras // Труды ИСА РАН, 2015. Т. 65. № 3. С. 85–93.
5. Arlazarov V.V., Zhukovskiy A., Krivtsov V., Nikolaev D., Polevoy D. Analiz osobennostey ispolzovaniya statsionarnykh i  mobilnykh malorazmernykh tsifrovykh video kamer dlya raspoznavaniya dokumentov // Informatsionnye tekhnologii i  vychislitelnye sistemy. 2014. № 3. C. 71–78.
6. Xiangrong Chen and Yuille A. L., “Detecting and reading text in natural scenes,” Proceedings of the IEEE Computer Society  Conference on Computer Vision and Pattern Recognition, 2004, pp. II-366-II-373 Vol.2.
7. Kwon Y., Kim J., “Recognition based Verification for the Machine Readable Travel Documents,” in International Workshop on  Graphics Recognition (GREC 2007), Curitiba, Brazil, September 20-21, 2007
8. Kwang-Baek Kim and Sungshin Kim. A passport recognition and face verification using enhanced fuzzy ART based RBF  network and PCA algorithm // Neurocomputing. 2008. 71, 16-18 (October 2008), 3202-3210.
9. Martín-Rodríguez F., “Automatic optical reading of passport information,” 2014 International Carnahan Conference on  Security Technology (ICCST), Rome, 2014, pp. 1-4.
10. Lee H. and Kwak N., “Character recognition for the machine reader zone of electronic identity cards,” 2015 IEEE  International Conference on Image Processing (ICIP), Quebec City, QC, 2015, pp. 387-391.
11. Hartl A., Arth C., Schmalstieg D. Real-time Detection and Recognition of Machine-Readable Zones with Mobile Devices.  VISAPP 2015 - 10th International Conference on Computer Vision Theory and Applications; Proceedings. 3. 79-87.
12. Lepetit V., Fua P. Towards Recognizing Feature Points using Classification Trees // Technical Report IC/2004/74. École  polytechnique fédérale de Lausanne. 2004.
13. Nikolaev D.P., Nikolaev I.P., Nikolaev P.P., Karpenko S.M., “Hough transform: underestimated tool in the computer vision  field”, European Conference on Modelling and Simulation 22. 2008.
14. Smart 3D OCR MRZ v.1.0
15. Order of the Federal Migration Service of the Russian Federation of June 30, 2011 No 279 “About approval of the rules and  method of forming machine-readable zone in the passport of a citizen of the Russian Federation, main identity document of the  citizen of the Russian Federation in the territory of the Russian Federation.” 



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