Fast projective image rectification for planar objects with Manhattan structure

J. Shemiakina; I. Konovalenko; D. Tropin; I. Faradjev

doi:10.1117/12.2559630

31 January 2020 Fast projective image rectification for planar objects with Manhattan structure

J. Shemiakina, I. Konovalenko, D. Tropin, I. Faradjev

Author Affiliations +

Proceedings Volume 11433, Twelfth International Conference on Machine Vision (ICMV 2019); 114331N (2020) https://doi.org/10.1117/12.2559630
Event: Twelfth International Conference on Machine Vision, 2019, Amsterdam, Netherlands

Abstract

This paper presents a method for metric rectification of planar objects that preserves angles and length ratios. An inner structure of an object is assumed to follow the laws of Manhattan World i.e. the majority of line segments are aligned with two orthogonal directions of the object. For that purpose we introduce the method that estimates the position of two vanishing points corresponding to the main object directions. It is based on an original optimization function of segments that estimates a vanishing point position. For calculation of the rectification homography with two vanishing points we propose a new method based on estimation of the camera rotation so that the camera axis is perpendicular to the object plane. The proposed method can be applied for rectification of various objects such as documents or building facades. Also since the camera rotation is estimated the method can be employed for estimation of object orientation (for example, during a surgery with radiograph of osteosynthesis implants). The method was evaluated on the MIDV-500 dataset containing projectively distorted images of documents with complex background. According to the experimental results an accuracy of the proposed method is better or equal to the-state-of-the-art if the background occupies no more than half of the image. Runtime of the method is around 3ms on core i7 3610qm CPU.

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J. Shemiakina, I. Konovalenko, D. Tropin, and I. Faradjev "Fast projective image rectification for planar objects with Manhattan structure", Proc. SPIE 11433, Twelfth International Conference on Machine Vision (ICMV 2019), 114331N (31 January 2020); https://doi.org/10.1117/12.2559630

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