Novel fractional-order Jacobi moments and invariant moments for pattern recognition applications

2021 ◽  
Author(s):  
Omar El Ogri ◽  
Hicham Karmouni ◽  
Mohamed Yamni ◽  
Mhamed Sayyouri ◽  
Hassan Qjidaa ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Fractional Order ◽  
Invariant Moments

New fractional-order Legendre-Fourier moments for pattern recognition applications

2020 ◽  
Vol 103 ◽  
pp. 107324 ◽  
Author(s):  
Khalid M Hosny ◽  
Mohamed M Darwish ◽  
Tarek Aboelenen
Keyword(s):  
Pattern Recognition ◽  
Fractional Order

New set of fractional-order generalized Laguerre moment invariants for pattern recognition

2020 ◽  
Vol 79 (31-32) ◽  
pp. 23261-23294 ◽  
Author(s):  
O. El Ogri ◽  
A. Daoui ◽  
M. Yamni ◽  
H. Karmouni ◽  
M. Sayyouri ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Fractional Order ◽  
Moment Invariants

scholarly journals Hybrid processor to compute invariant moments for pattern recognition

1980 ◽  
Vol 5 (9) ◽  
pp. 395 ◽  
Author(s):  
David Casasent ◽  
Demetri Psaltis
Keyword(s):  
Pattern Recognition ◽  
Invariant Moments

COMPLEX FUNCTION PROJECTIVE SYNCHRONIZATION IN FRACTIONAL-ORDER COMPLEX NETWORKS AND ITS APPLICATION IN FRACTAL PATTERN RECOGNITION

2019 ◽  
Vol 22 (05) ◽  
pp. 1950010
Author(s):  
XIAORAN LIN ◽  
SHANGBO ZHOU ◽  
LIHUI SUN ◽  
YALI WU
Keyword(s):  
Pattern Recognition ◽  
Complex Networks ◽  
Fractional Order ◽  
Complex Function ◽  
Human Perception ◽  
Projective Synchronization ◽  
Order Complex ◽  
Fractal Pattern ◽  
Perception System ◽  
Synchronization Scheme

Based on the stability theory of fractional-order systems, a projective synchronization scheme with different coefficients is realized in [Formula: see text] complex networks to build a model for fractal pattern recognition. In the proposed complex function projection synchronization scheme, first a drive-response network is constructed with [Formula: see text] fractional-order complex nodes; And then reasonable controllers are designed to realize the function projection synchronization with different projection coefficients, which are used to encode the fractal pattern; Finally, using the synchronization error system, the input variables for identifying fractal patterns can be solved, and the fractal pattern can be recognized. From the perspective of neurodynamics, the proposed model provides a better understanding of human perception system.

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