Calculation of a Vanishing Point by the Maximum Likelihood Estimation Method

Bulletin of the South Ural StateUniversity. Ser. Mathematical Modelling, Programming & ComputerSoftware (Bulletin SUSU MMCS), 2020, vol. 13, no. 1, pp. 107–117

The paper presents a method to estimate the position of the vanishing point of a set of converging noisy segments. As a model of segment noise, we use normal noise applied to the end points of the segment. We construct a functional that depends on the position of the considered segments and determine the vanishing point as the point at which the functional reaches its minimum. In order to set such a functional, we use the maximum likelihood estimation method. The obtained functional allows both to pose the problem on numerical minimization and to set the function of correspondence of the segment to the beam, if it is necessary to filter out the emission segments from the initial set. The application of the proposed method is illustrated by the example of correction of projective distortions and the subsequent localization of the pages of the Russian Federation passport on the images of the passport pages. In the framework of this problem, we assume that the segments highlighted in an image correspond to several beams and contain emissions. In order to ensure stability and ability to estimate a set of vanishing points, we propose an algorithm based on the RANSAC scheme. The use of the projective normalization method allows to reduce the number of page localization errors from 6,4% to 1,8%.

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

Send Request

Send request for quotation or more information about products.

Contact Form

Smart Engines is to provide a reply within 2 business days. If you don't receive a message from our representative within 2 business days, please check your spam folder or simply send us an email to sales@smartengines.com

Smart Engines is committed to privacy, we are fully compliant with GDPR and CCPA, all the personal data is intended for internal use only.