Просматривается номер   2018-S1
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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
V.V. Arlazarov, D.P. Matalov, S.A. Usilin Localization of the seal on the identity document image using machine learning approach

Abstract.

In this paper, the novel method for solving circular seal detection problem based on extended Viola-Jones algorithm is presented. The method's performance is demonstrated during solving the problem of government seal stamp localization on the second page of the passport of Russian Federation. The method is scalable and can be used for different detection problems.

Keywords:

machine learning, object detection, Viola-Jones cascades, digital image processing, document image recognition, forensics.

PP. 158-166.

DOI: 10.14357/20790279180518

References

1. Arlazarov V.L., Slavin O.A. Algoritmy raspoznavaniya i tekhnologii vvoda tekstov v EHVM. – Informacionnye tekhnologii i vychislitel’nye sistemy № 1. 1996. Vol. 6. P. 48 – 54
2. Arlazarov V.V, Postnikov V.V., SHolomov D.L. Cognitive Forms – sistema massovogo vvoda strukturirovannyh dokumentov. // Upravlenie informacionnymi potokami. M: EHditorial URSS, 2002. P. 37–49.
3. Usilin S.A., Nikolaev D.P., Postnikov V.V. Cognitive PDF/A – tekhnologiya ocifrovki tekstovyh dokumentov dlya publikacii v Internet i dolgovremennogo arhivnogo hraneniya // Trudy Instituta sistemnogo analiza RAN. Tekhnologii programmirovaniya i hraneniya dannyh / pod red. Arlazarov V.L., Emel’yanov N.E. M.: LENAND, 2009. Vol. 45. P. 159–173.
4. K. Bulatov, V.V. Arlazarov, T. Chernov, O. Slavin, D. Nikolaev. SmartIDReader: Document recognition in video stream // 14th IAPR International Conference on Document Analysis and Recognition (ICDAR). IEEE. 2017. Vol 6, P. 39–44. DOI: 10.1109/ ICDAR.2017.347.
5. Bezmaternyh P.V., Nikolaev D.P., Postnikov V.V. Bystryj algoritm detektirovaniya rukopisnyh pometok // Trudy Instituta sistemnogo analiza. 2008. Vol.38. P. 185 – 193.
6. Kuroptev A.V., Nikolaev D.P., Postnikov V.V. Vydelenie graficheskih primitivov i tekstovyh blokov na izobrazheniyah dokumentov s pomoshch’yu morfologicheskih operacij // Trudy 51-j nauchnoj konferencii MFTI «Sovremennye problemy fundamental’nyh i prikladnyh nauk». CHast’ IX. Innovacii i vysokie tekhnologii. M.: MFTI, 2008. P. 29–32.
7. Partha Pratim Roy, Umapada Pal, Josep Llados. Seal Detection and Recognition: An Approach for Document Indexing // 10th International Conference on Document Analysis and Recognition. 2015. Vol. 2015, Article ID 367879. 15 p. DOI: 10.1109/ICDAR.2009.128.
8. Partha Pratim Roy, Umapada Pal, Josep Llados. Document Seal Detection using GHT and Character Proximity Graphs // Pattern Recognition. 2011. Vol. 44. № 6. P. 1282-1295.
9. Guangyu Zhu, Stefan Jaeger, David Doermann. A robust stamp detection framework on degraded documents // Document Recognition and Retrieval XIII. 2006. 60670B. 9 p. DOI: 10.1117/12.643537.
10. D. Ballard. Generalizing the Hough transform to detect arbitrary shapes // Pattern Recognition. 1987. Vol. 13. № 2. P. 111-122. DOI: 10.1016/0031-3203(81)90009-1.
11. D.P. Nikolaev, S.M. Karpenko, I.P. Nikolaev and P.P Nikolayev. Hough Transform: Underestimated Tool in the Computer Vision Field // Proceedings of 22nd European Conference on Modelling and Simulation (ECMS 2008). 2008. P. 238-243. DOI: 10.7148/2008-0238.
12. Sheraz Ahmed, Faisal Shafait, Marcus Liwicki, Andreas Dengel. A Generic Method for Stamp Segmentation Using Part-Based Features // 12th International Conference on Document Analysis and Recognition. 2013. P. 708-712. DOI: 10.1109/ICDAR.2013.145.
13. Ning Ding, Xue-dong Zhang, Zhi-feng Wang, Chuan Wan. Seal Identification based on SIFT and Edge Direction Histogram // The 9th International Conference on Computer Science & Education. 2014. Vol. 42. № 10. P. 357-361. DOI: 10.1109/ICCSE.2014.6926485.
14. Bo Jin, Haiying Wang. Seal registration and identification based on SIFT // IEEE Proceedings of the International Conference on Anti-Counterfeiting Security and Identification. 2016.P. 97-100. DOI: 10.1109/ICASID.2015.7405669.
15. Katsuhiko Ueda. Extraction of signature ad seal imprint from bankchecks by using color information // Proceedings of 3rd International Conference on Document Analysis and Recognition. 1995. P. 665-668. DOI: 10.1109/ICDAR.1995.601983.
16. Barbora Micenkova, Joost van Beusekom, Faisal Shafait. Stamp Verification for Automated Document Authentication // International Workshop on Computational Forensics 2014: Computational Forensics. 2015. P. 117-129.
17. Usilin S., Nikolaev D., Postnikov V. Structural Compression of Document Images with PDF/A // Proceedings of «24th European Conference on Modelling and Simulation ECMS 2010». Kuala Lumpur, 2010. P. 242–246. DOI: 10.7148/2010-0242-0246
18. Paweł Forczmański, Andrzej Markiewicz. Stamps Detection and Classification Using Simple Features Ensemble // Mathematical Problems in Engineering. 2015. Vol. 2015. Article ID 367879.15 p. DOI: 10.1155/2015/367879.
19. Saraev A.A., Nikolaev D.P. Vydelenie graficheskih primitivov dlya analiza struktury dokumenta na primere lokalizacii pechatej // Informacionnye tekhnologii i sistemy. 2012. P. 371-376.
20. Viola P., Jones M. Robust Real-time Object Detection // International Journal of Computer Vision. 2002.
21. Usilin S.A., Nikolaev D.P., SHolomov D.L., Arlazarov V.V. Raspoznavanie gil’oshirnyh ehlementov: opredelenie stranic pasporta RF // Trudy ISA RAN. 2013. Vol. 63 № 3. P. 106-110.
22. Kuznetsova E.G., Usilin S.A., Minkina A.G., Nikolaev D.P. Modifikatsiya slabih klassifikatorov mashini Violi-Dzhonsa dlya mul’tispektral’nih izobrazhenii // Informatsionnie tehnologii i sistemi (ITiS’15): sbornik trudov konferentsii. 2015. P. 329–337.
23. Zhukovskii A.E., Tarasova N.A., Usilin S.A., Nikolaev D.P. Sintez obuchayuschei viborki na osnove real’nih dannih v zadachah raspoznavaniya izobrazhenii // Informatsionnie tehnologii i sistemi (ITiS’12): sbornik trudov konferentsii. M., 2012. P. 377–382.
 
     
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