New fractional-order shifted Gegenbauer moments for image analysis and recognition

Khalid M. Hosny, Mohamed M. Darwish, Mohamed Meselhy Eltoukhy

Research output: Contribution to journalReview articlepeer-review

8 Scopus citations


Orthogonal moments are used to represent digital images with minimum redundancy. Orthogonal moments with fractional-orders show better capabilities in digital image analysis than integer-order moments. In this work, the authors present new fractional-order shifted Gegenbauer polynomials. These new polynomials are used to define a novel set of orthogonal fractional-order shifted Gegenbauer moments (FrSGMs). The proposed method is applied in gray-scale image analysis and recognition. The invariances to rotation, scaling and translation (RST), are achieved using invariant fractional-order geometric moments. Experiments are conducted to evaluate the proposed FrSGMs and compare with the classical orthogonal integer-order Gegenbauer moments (GMs) and the existing orthogonal fractional-order moments. The new FrSGMs outperformed GMs and the existing orthogonal fractional-order moments in terms of image recognition and reconstruction, RST invariance, and robustness to noise.

Original languageEnglish
Pages (from-to)57-66
Number of pages10
JournalJournal of Advanced Research
StatePublished - Sep 2020


  • Fractional-order shifted Gegenbauer moments
  • Geometric transformations
  • Image analysis
  • Image recognition
  • Image reconstruction


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