Журнал «Труды Института системного анализа Российской академии наук» - O.O. Petrova, K.B. Bulatov Methods of machine-readable zone recognition results post-processing

Просматривается номер 2018-S1

Data mining and image recognition

N.S. Skoryukina, A.N. Milovzorov, D.V. Polevoy, V.V. Arlazarov Paintings recognition in uncontrolled conditions using one-shot learning

A.E. Zhukovsky Methods for interframe integration of document detection results in a video stream of a mobile device

I.A. Kunina, E. I. Panfilova, M.A. Povolotskiy Zebra-crossing detection on road images using dynamic time warping

O.A. Slavin, V.L. Arlazarov Method for classifying recognized pages of administrative documents on the basis of text key points

O.O. Petrova, K.B. Bulatov Methods of machine-readable zone recognition results post-processing

A.E. Marchenko, E.I. Ershov, D.A. Shepelev, D.S. Sidorchuk, V.P. Bozhkova, D.P. Nikolaev Designing of language of description of observable properties of recognized objects in the absence of samples

Intellectual systems and technologies

E.E. Limonova, N.L. Rzhenev, A.V. Uskov, M.I. Neiman-zade Fast implementation of Hamming distance on VLIW-architectures on the example of Elbrus platform

V.V. Arlazarov, K.B. Bulatov, A.V. Uskov A model of object recognition system in video stream of a mobile device

A.A. Ivanova, S.A. Gladilin, A.E. Zhukovsky, E.L. Pliskin Database for the administrative accounting of scientific publications

A.S. Ingacheva, A.V. Sheshkus, T. S. Chernov, E.E. Limonova, V.V. Arlazarov X-ray computed tomography scanner – a new tool in recognition

N.O. Beshaposhnikov, A.G. Kushnirenko, A.A. Levin A method for auto-calibration of the educational robot control parameters using computer vision library OpenCV

Image and signal processing

A.E. Zhukovsky, E.E. Limonova, D.P. Nikolaev Exact implementation of common image processing algorithms using fully convolutional networks

V.E. Prun Reducing the influence of high-absorbing inclusions on CT reconstructions using algebraic reconstruction technique

B.I. Savelyev, I.B. Mamay, D.P. Nikolaev, V.L. Arlazarov, K.B. Bulatov, N.S. Skoryukina A method of projective transformations graph adjustment for panorama stitching problem for images of planar objects

D.V. Tropin, D.P. Nikolaev, D.G. Slugin The method of image alignment based on sharpness maximization

J.A. Shemiakina, A.E. Zhukovsky, I.A. Konovalenko, D.P. Nikolaev Algorithm for automatic framing of digital images under projective transformation

MACHINE LEARNING

A.V. Gayer, A.V. Sheshkus, Y.S. Chernyshova Augmentation on the fly for the neural networks learning

V.V. Arlazarov, D.P. Matalov, S.A. Usilin Localization of the seal on the identity document image using machine learning approach

A.E. Lynchenko, A.V.Sheshkus, V.L.Arlazarov Identity document classifiaction algorithm based on similarity metric robust to projective distortions

V.A. Malykh, V.A. Lyalin On Classification of Noisy Texts

Y.S. Chernyshova, M.A. Aliev, A.V. Sheshkus Optical font recognition of images captured with mobile devices and its application for detecting identity documents forgery

D.A. Ilin Fast words boundaries localization in text fields for low quality document images

D.E. Ivanov, D.V. Polevoy, D.L. Sholomov Selection of informative elements for the training of a lightweight convolutional neural network classifier in the conditions of a strong imbalance of the training sample


	O.O. Petrova, K.B. Bulatov Methods of machine-readable zone recognition results post-processing
Abstract. In this paper a task of correction (post-processing) of machine-readable zone recognition results is discussed. A survey is presented for existing approaches of recognition error correction methods and an algorithm is proposed for applying these methods for machine-readable zone post-processing. Experimental results are shown for the described methods. Keywords: documents recognition, MRZ, recognition results correction. PP. 43-50. DOI: 10.14357/20790279180505 References 1. Bessmeltsev V., Bulushev E., Goloshevsky N. High-speed OCR algorithm for portable passport readers// Graphicon’11. 2011. P. 25–29. 2. Slugin D.G. Properties of context-based recognition of Russian international passport in Cognitive Passport. // Proc. ISA RAS, V. 45, 2009. P.174-182. 3. Sholomov D.L., Postnikov V.V., Marchenko A.A., Uskov A.V. Post-processing of OCR Results Using Automatically Constructed Partially Defined Syntax. // Proceedings of the Institute for System Analysis RAS, Vol. 16. pp. 146-163, 2005. 4. ICAO Doc 9303 Part 3: Specifications Common to all MRTDs. 2015. Machine Readable Travel Documents – International Civil Aviation Organization. 5. Bouchaffra D., Govindaraju V., Srihari S. N. Postprocessing of Recognized Strings Using Nonstationary Markovian Models // IEEE Transactions on Pattern Analysis and Machine Intelligence. 1997. V. 21. № 10, Р. 990–999. 6. Kukich K. Techniques for Automatically Correcting Words in Text // ACM computing survey, Computational Linguistics. 1992. V. 24. № 4, Р. 377–439. 7. Youssef Bassil, Mohammad Alwani. OCR postprocessing error correction algorithm using Google’s online spelling suggestion. // Journal of Emerging Trends in Computing and Information Sciences, 3(1): 90–99. 8. Bulatov K.B., Nikolaev D.P., Postnikov V.V. General-purpose algorithm for text field OCR result post-processing based on validation grammars // Proceedings of the Institute for System Analysis RAS, Vol. 65(4). pp. 68-73, 2015. 9. Mercer J. Errors in travel documents. // Keesing Journal of Documents& Identity, issue 34, Feb 2011. Available at: http://keesingjournalofdocuments.com/content/Cases_analysed/KJDI_2011_34_ Mercer.pdf (accessed June 22, 2018). 10. Bulatov K.B., Polevoy D.V., Ilin D.A., Chernyshova Y.S. Problems of machine-readable zone recognition captured with digital mobile cameras//Proceedings of the Institute for System Analysis RAS, Vol. 65(3). pp. 85-93, 2015. 11. Arlasarov V.V., Zhukovsky A.E., Krivtsov V.E., Nikolaev D.P., Polevoy D.V. Analysis of features of the use of fixed and mobile small-sized digital video camera for OCR // Proceedings of the Institute for System Analysis RAS, Vol. 64(3). pp. 71-81, 2014. 12. Dong Xiao Ni. Application of Neural Networks to Character Recognition // Proceedings of Students/ Faculty Research Day, CSIS, Pace University, May 4th, 2007.

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