Rotation-invariant color pattern recognition based on the joint fractional Fourier transform correlator

2007 ◽  
Author(s):  
Yupei Zhang ◽  
Weimin Jin
Keyword(s):  
Pattern Recognition ◽  
Fourier Transform ◽  
Fractional Fourier Transform ◽  
Color Pattern ◽  
Rotation Invariant

Rotation invariant color pattern recognition by use of a three-dimensional Fourier transform

2003 ◽  
Vol 42 (8) ◽  
pp. 1434 ◽  
Author(s):  
Oscar Gualdrón ◽  
Josep Nicolás ◽  
Juan Campos ◽  
Maria J. Yzuel
Keyword(s):  
Pattern Recognition ◽  
Fourier Transform ◽  
Three Dimensional ◽  
Color Pattern ◽  
Rotation Invariant

INVARIANT PATTERN RECOGNITION USING RIDGELET PACKETS AND THE FOURIER TRANSFORM

2009 ◽  
Vol 07 (02) ◽  
pp. 215-228 ◽  
Author(s):  
G. Y. CHEN ◽  
P. BHATTACHARYA
Keyword(s):  
Pattern Recognition ◽  
Fourier Transform ◽  
State Of The Art ◽  
Experimental Results ◽  
Noisy Environments ◽  
Rotation Invariant ◽  
Pattern Recognition Techniques ◽  
Orthonormal Bases ◽  
The Fourier Transform ◽  
Very High

In this paper, we propose two novel invariant algorithms for pattern recognition by using ridgelet packets and the Fourier transform. Ridgelet packets provide many orthonormal bases that can effectively capture directional features present in pattern images. The Fourier transform is good at eliminating the orientation differences. By combining these two tools, very efficient rotation invariant pattern recognition techniques are created. Experimental results show that the proposed methods achieve very high classification rates and they outperform other state-of-the-art methods for rotation invariant pattern recognition under both noise-free and noisy environments.

scholarly journals Fractional Fourier Transform for Ultrasonic Chirplet Signal Decomposition

2012 ◽  
Vol 2012 ◽  
pp. 1-13 ◽  
Author(s):  
Yufeng Lu ◽  
Alireza Kasaeifard ◽  
Erdal Oruklu ◽  
Jafar Saniie
Keyword(s):  
Experimental Data ◽  
Pattern Recognition ◽  
Fourier Transform ◽  
Parameter Estimation ◽  
Fractional Fourier Transform ◽  
Signal Decomposition ◽  
Chirp Rate ◽  
Rate Parameter ◽  
Ultrasonic Signals ◽  
The Relationship

A fractional fourier transform (FrFT) based chirplet signal decomposition (FrFT-CSD) algorithm is proposed to analyze ultrasonic signals for NDE applications. Particularly, this method is utilized to isolate dominant chirplet echoes for successive steps in signal decomposition and parameter estimation. FrFT rotates the signal with an optimal transform order. The search of optimal transform order is conducted by determining the highest kurtosis value of the signal in the transformed domain. A simulation study reveals the relationship among the kurtosis, the transform order of FrFT, and the chirp rate parameter in the simulated ultrasonic echoes. Benchmark and ultrasonic experimental data are used to evaluate the FrFT-CSD algorithm. Signal processing results show that FrFT-CSD not only reconstructs signal successfully, but also characterizes echoes and estimates echo parameters accurately. This study has a broad range of applications of importance in signal detection, estimation, and pattern recognition.

Pattern recognition using binary masks based on the fractional Fourier transform

2018 ◽  
Vol 65 (14) ◽  
pp. 1634-1657 ◽  
Author(s):  
Esbanyely Garza-Flores ◽  
Josué Álvarez-Borrego
Keyword(s):  
Pattern Recognition ◽  
Fourier Transform ◽  
Fractional Fourier Transform

A New Study of Shape and Size-dependent Properties of Nanocrystals Utilizing the Fractional Fourier Transform

2020 ◽  
Vol 5 (2) ◽  
pp. 165-174
Author(s):  
Aeshah Salem
Keyword(s):  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Fourier Transform Infrared Spectroscopy ◽  
Surface Area ◽  
Fractional Fourier Transform ◽  
Fourier Transform Infrared ◽  
Chemical Dynamics ◽  
Znse Nanoparticles ◽  
Size Dependent ◽  
Shape And Size

Background: Possessions of components, described by their shape and size (S&S), are certainly attractive and has formed the foundation of the developing field of nanoscience. Methods: Here, we study the S&S reliant on electronic construction and possession of nanocrystals by semiconductors and metals to explain this feature. We formerly considered the chemical dynamics of mineral nanocrystals that are arranged according to the S&S not only for the big surface area, but also as a consequence of the considerably diverse electronic construction of the nanocrystals. Results: The S&S of models, approved by using the Fractional Fourier Transform Infrared Spectroscopy (FFTIR), indicate the construction of CdSe and ZnSe nanoparticles. Conclusion: In order to study the historical behavior of the nanomaterial in terms of S&S and estimate further results, the FFTIR was used to solve this project.

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