December 9, 2017

Algorithms for correcting recognition results using N-grams

Pattern Recognit. Image Anal. 27, 832–837 (2017). https://doi.org/10.1134/S1054661817040125

This paper studies the application of N-grams for correcting the results of pattern recognition of words in documents based on the example of recognition of passport fields of a citizen of the Russian Federation. Three algorithms for correcting recognition results are given for trigrams. One of them is based on the use of trigram probabilities in combination with evaluation of recognition. The other algorithms are based on the definition of marginal distributions and computations by means of graphical probability models. The results of experiments on the application of the algorithms and comparison of the characteristics of the algorithms are presented.

Test Drive Our Smart Engines

Free demo apps allow you to experience the power of Smart Engines software for intelligent document scanning in a real-world context.

Why not experience the power of Smart Engines for yourself? Our demo apps allow you to test the capabilities of our identity document recognition software on mobile devices in videostream or in a single image (photo, scan).

Simply display any document to the camera in real-time or choose a photo from the gallery, and the app will recognize and capture the necessary data.

Demo apps Privacy Policy

id documents enginge by Smart Engines
Apple App Store Badge
Google Play Badge
id documents enginge by Smart Engines

Get in Touch

For questions about our products, research, people or project proposals, please get in touch.

Contact Form
Warning before submitting your request:

Smart Engines is fully committed to provide an answer within 2 working days. However, it is your responsibility that your IT infrastructure does not block our reply or redirect it into your spams. If you haven’t received any answer from us within 2 working days, please check your spams or simply call us.

Smart Engines guarantees that the provided information will not be made public and will be used only internally.