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Journal of Electrical and Computer Engineering
Volume 2017 (2017), Article ID 6142795, 9 pages
Research Article

Epipolar Plane Image Rectification and Flat Surface Detection in Light Field

School of Computer Science, Northwestern Polytechnical University, Xi’an 710072, China

Correspondence should be addressed to Qing Wang

Received 13 April 2017; Revised 9 July 2017; Accepted 7 August 2017; Published 19 September 2017

Academic Editor: Panajotis Agathoklis

Copyright © 2017 Lipeng Si et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Flat surface detection is one of the most common geometry inferences in computer vision. In this paper we propose detecting printed photos from original scenes, which fully exploit angular information of light field and characteristics of the flat surface. Unlike previous methods, our method does not need a prior depth estimation. The algorithm rectifies the mess epipolar lines in the epipolar plane image (EPI). Then feature points are extracted from light field data and used to compute an energy ratio in the depth distribution of the scene. Based on the energy ratio, a feature vector is constructed and we obtain robust detection of flat surface. Apart from flat surface detection, the kernel rectification algorithm in our method can be expanded to inclined plane refocusing and continuous depth estimation for flat surface. Experiments on the public datasets and our collections have demonstrated the effectiveness of the proposed method.