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Paper
13 April 2018 Document localization algorithms based on feature points and straight lines
Author Affiliations +
Proceedings Volume 10696, Tenth International Conference on Machine Vision (ICMV 2017); 106961H (2018) https://doi.org/10.1117/12.2311478
Event: Tenth International Conference on Machine Vision, 2017, Vienna, Austria
Abstract
The important part of the system of a planar rectangular object analysis is the localization: the estimation of projective transform from template image of an object to its photograph. The system also includes such subsystems as the selection and recognition of text fields, the usage of contexts etc. In this paper three localization algorithms are described. All algorithms use feature points and two of them also analyze near-horizontal and near- vertical lines on the photograph. The algorithms and their combinations are tested on a dataset of real document photographs. Also the method of localization quality estimation is proposed that allows configuring the localization subsystem independently of the other subsystems quality.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Natalya Skoryukina, Julia Shemiakina, Vladimir L. Arlazarov, and Igor Faradjev "Document localization algorithms based on feature points and straight lines", Proc. SPIE 10696, Tenth International Conference on Machine Vision (ICMV 2017), 106961H (13 April 2018); https://doi.org/10.1117/12.2311478
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CITATIONS
Cited by 8 scholarly publications and 1 patent.
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KEYWORDS
Detection and tracking algorithms

Cameras

Image processing

Photography

Target detection

Analytical research

Binary data

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