PALMPRINT IDENTIFICATION BY FOURIER TRANSFORM

Author(s):  
WENXIN LI ◽  
DAVID ZHANG ◽  
ZHUOQUN XU

Palmprint identification refers to searching in a database for the palmprint template, which is from the same palm as a given palmprint input. The identification process involves preprocessing, feature extraction, feature matching and decision-making. As a key step in the process, in this paper, we propose a new feature extraction method by converting a palmprint image from a spatial domain to a frequency domain using Fourier Transform. The features extracted in the frequency domain are used as indexes to the palmprint templates in the database and the searching process for the best match is conducted by a layered fashion. The experimental results show that palmprint identification based on feature extraction in the frequency domain is effective in terms of accuracy and efficiency.

2021 ◽  
Vol 63 (8) ◽  
pp. 465-471
Author(s):  
Shang Zhiwu ◽  
Yu Yan ◽  
Geng Rui ◽  
Gao Maosheng ◽  
Li Wanxiang

Aiming at the local fault diagnosis of planetary gearbox gears, a feature extraction method based on improved dynamic time warping (IDTW) is proposed. As a calibration matching algorithm, the dynamic time warping method can detect the differences between a set of time-domain signals. This paper applies the method to fault diagnosis. The method is simpler and more intuitive than feature extraction methods in the frequency domain and the time-frequency domain, avoiding their limitations and disadvantages. Due to the shortcomings of complex calculation, singularity and poor robustness, the paper proposes an improved method. Finally, the method is verified by envelope spectral feature analysis and the local fault diagnosis of gears is realised.


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