Robust Iris Feature Extraction using Dual Tree Complex Wavelet Transform

2007 ◽  
Author(s):  
A. S. Narote ◽  
S. P. Narote ◽  
L. M. Waghmare ◽  
M. B. Kokare
Keyword(s):  
Feature Extraction ◽  
Wavelet Transform ◽  
Complex Wavelet Transform ◽  
Complex Wavelet ◽  
Iris Feature Extraction

CONTOUR-BASED FEATURE EXTRACTION USING DUAL-TREE COMPLEX WAVELETS

2007 ◽  
Vol 21 (07) ◽  
pp. 1233-1245 ◽  
Author(s):  
G. Y. CHEN ◽  
W. F. XIE
Keyword(s):  
Feature Extraction ◽  
Fourier Transform ◽  
Wavelet Transform ◽  
Invariant Property ◽  
Complex Wavelet Transform ◽  
Translation Invariant ◽  
Feature Extraction Method ◽  
Complete Representation ◽  
Complex Wavelet ◽  
The Fourier Transform

A contour-based feature extraction method is proposed by using the dual-tree complex wavelet transform and the Fourier transform. Features are extracted from the 1D signals r and θ, and hence the processing memory and time are reduced. The approximate shift-invariant property of the dual-tree complex wavelet transform and the Fourier transform guarantee that this method is invariant to translation, rotation and scaling. The method is used to recognize aircrafts from different rotation angles and scaling factors. Experimental results show that it achieves better recognition rates than that which uses only the Fourier features and Granlund's method. Its success is due to the desirable shift invariant property of the dual-tree complex wavelet transform, the translation invariant property of the Fourier spectrum, and our new complete representation of the outer contour of the pattern.

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