Paper
21 June 2015 Stereo matching based on census transformation of image gradients
C. Stentoumis, L. Grammatikopoulos, I. Kalisperakis, G. Karras, E. Petsa
Author Affiliations +
Abstract
Although multiple-view matching provides certain significant advantages regarding accuracy, occlusion handling and radiometric fidelity, stereo-matching remains indispensable for a variety of applications; these involve cases when image acquisition requires fixed geometry and limited number of images or speed. Such instances include robotics, autonomous navigation, reconstruction from a limited number of aerial/satellite images, industrial inspection and augmented reality through smart-phones. As a consequence, stereo-matching is a continuously evolving research field with growing variety of applicable scenarios. In this work a novel multi-purpose cost for stereo-matching is proposed, based on census transformation on image gradients and evaluated within a local matching scheme. It is demonstrated that when the census transformation is applied on gradients the invariance of the cost function to changes in illumination (non-linear) is significantly strengthened. The calculated cost values are aggregated through adaptive support regions, based both on cross-skeletons and basic rectangular windows. The matching algorithm is tuned for the parameters in each case. The described matching cost has been evaluated on the Middlebury stereo-vision 2006 datasets, which include changes in illumination and exposure. The tests verify that the census transformation on image gradients indeed results in a more robust cost function, regardless of aggregation strategy.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
C. Stentoumis, L. Grammatikopoulos, I. Kalisperakis, G. Karras, and E. Petsa "Stereo matching based on census transformation of image gradients", Proc. SPIE 9528, Videometrics, Range Imaging, and Applications XIII, 95280Q (21 June 2015); https://doi.org/10.1117/12.2184763
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Binary data

Image filtering

Algorithm development

Photogrammetry

Reconstruction algorithms

Augmented reality

Image acquisition

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