Automated photo‐consistency test for voxel colouring based on fuzzy adaptive hysteresis thresholding. Issue 8 (1st November 2013)

• Record Type: Journal Article
• Authors: Barhoumi, Walid; Bakkay, Mohamed Chafik; Zargouba, Ezzeddine
• Is Part Of: IET image processing. Volume 7:Issue 8(2013)
• Page Start: 713
• Page End: 724
• Publication Date: 2013-11-01
• Subjects: calibration -- fuzzy set theory -- image colour analysis -- image reconstruction -- image segmentation; automated photoconsistency test -- voxel colouring -- fuzzy adaptive hysteresis thresholding -- image reconstruction -- three‐dimensional surface model -- calibration -- image thresholding -- spatial coherence -- volume reconstruction -- floating voxel -- volumetric scene reconstruction; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2013.0098
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract : Voxel colouring is a popular method for reconstructing a three‐dimensional surface model from a set of a few calibrated images. However, the reconstruction quality is largely dependent on a thresholding procedure allowing the authors to decide, for each voxel, whether it is photo‐consistent or not. Nevertheless, in addition to the absence of any information on the neighbouring voxels during the photo‐consistency test, it is extremely difficult to define the appropriate thresholds, which should be precise and stable on all surface voxels. In this study, the authors propose an automated photo‐consistency test based on fuzzy hysteresis thresholding. The proposed method allows the incorporation of the spatial coherence during volume reconstruction, while avoiding 'floating voxels' and holes. Moreover, the ambiguity of choosing the thresholds is extremely minimised by defining a fuzzy degree of membership of each voxel into the class of consistent voxels. Also, there is no need for preset thresholds since the hysteresis ones are defined automatically and adaptively depending on the number of images that the voxel is projected onto. Preliminary results are very promising and demonstrate that the proposed method performs automatically precise and smooth volumetric scene reconstruction.