DocumentCode :
3245337
Title :
Feature extraction using extended central projection
Author :
Lan, Rushi ; Yang, Jianwei ; Jiang, Yong ; Feng, Xiaoxia
Author_Institution :
Sch. of Math & Stat., Nanjing Univ. of Inf. Sci. & Technol., Nanjing, China
fYear :
2012
fDate :
15-17 July 2012
Firstpage :
327
Lastpage :
331
Abstract :
A novel feature extraction method is proposed in this paper. Dislike contour-based or region-based approaches, an object is first converted to a closed curve by extended central projection (ECP). The derived curve not only keeps the affine transform information, but also is very robust to noise. Then whitening transform is performed to the curve such that the affine transformation is simplified to a rotation only. Finally, Fourier transform are employed to remove the rotation. Several experiments have been conducted to evaluate the performance of the proposed method. Experimental results show that the proposed method has a powerful discrimination ability, and is more robust to noise.
Keywords :
Fourier transforms; affine transforms; feature extraction; object recognition; ECP; Fourier transform; affine transform information; contour-based approach; extended central projection; feature extraction method; object recognition; region-based approach; whitening transform; Accuracy; Covariance matrix; Feature extraction; Noise; Pattern recognition; Shape; Transforms; Affine transformation; Extended central projection (ECP); Feature extraction; Object recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wavelet Analysis and Pattern Recognition (ICWAPR), 2012 International Conference on
Conference_Location :
Xian
ISSN :
2158-5695
Print_ISBN :
978-1-4673-1534-0
Type :
conf
DOI :
10.1109/ICWAPR.2012.6294802
Filename :
6294802
Link To Document :
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