Institute of Information Theory and Automation

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Bibliography

Conference Paper (international conference)

3D Non-separable Moment Invariants

Flusser Jan, Suk Tomáš, Bedratyuk L., Karella Tomáš

: Computer Analysis of Images and Patterns. CAIP 2023, p. 295-305 , Eds: Tsapatsoulis N.

: Computer Analysis of Images and Patterns. CAIP 2023, (Limassol, CY, 20230925)

: GA21-03921S, GA ČR

: 3D recognition, 3D rotation invariants, non-separable moments, Appell polynomials

: 10.1007/978-3-031-44237-7_28

: http://library.utia.cas.cz/separaty/2023/ZOI/flusser-0575788.pdf

(eng): In this paper, we introduce new 3D rotation moment invariants, which are composed of non-separable Appell moments. The Appell moments can be substituted directly into the 3D rotation invariants instead of the geometric moments without violating their invariance. We show that non-separable moments may outperform the separable ones in terms of recognition power and robustness thanks to a better distribution of their zero surfaces over the image space. We test the numerical properties and discrimination power of the proposed invariants on three real datasets – MRI images of human brain, 3D scans of statues, and confocal microscope images of worms.

: JD

: 20206

2019-01-07 08:39