A face recognition algorithm based on compressive sensing and wavelets transform

Author

Yi-Zu Dong ; Shou-Ming Guo ; Kai Yang

Author_Institution

Sch. of Aeronaut. & Astronaut., Univ. of Electron. Sci& Technol. of China(UESTC), Chengdu, China

fYear

2013

fDate

17-19 Dec. 2013

Firstpage

58

Lastpage

61

Abstract

In face recognition, image brings great inconvenience to the hardware because its high degree of redundancy and a largequantity of data. This paper introduces a theory of Compressive Sensing(CS) for Face Recognition (CSFR) that a DWT is applied to the dictionary which created by all training samples, then the image is processed by CS in wavelet domain. The reconstruction is computed withOrthogonal Matching Pursuit(OMP) algorithm, and the residual(the distance between the reconstruction vector and the training vector) determines the class of thetest data. The computer experiment on ORL database shows that the CSFR algorithm based on DWT (DWT-CFSR) performs more robust and effective in face recognition than SRC and PCA algorithms.

Keywords

compressed sensing; convex programming; discrete wavelet transforms; face recognition; image coding; image reconstruction; learning (artificial intelligence); DWT; DWT-CFSR algorithm; OMP algorithm; ORL database; compressive sensing; dictionary; face recognition algorithm; image processing; orthogonal matching pursuit algorithm; reconstruction vector; training samples; training vector; wavelet domain; wavelet transform; Compressed sensing; Discrete wavelet transforms; Face; Face recognition; Matching pursuit algorithms; Sparse matrices; Training; CSFR; Compressive Sensing (CS); DWT; Face Recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Wavelet Active Media Technology and Information Processing (ICCWAMTIP), 2013 10th International Computer Conference on

Conference_Location

Chengdu

Print_ISBN

978-1-4799-2445-5

Type

conf

DOI

10.1109/ICCWAMTIP.2013.6716600

Filename

6716600