Face recognition using Oriented Laplacian of Gaussian (OLOG) and Independent Component Analysis (ICA)

Author

Karande, Kailash J. ; Talbar, Sanjay N. ; Inamdar, Sandeep S.

Author_Institution

SKN Sinhgad Coll. of Eng., Pandharpur, India

fYear

2012

fDate

16-18 May 2012

Firstpage

99

Lastpage

103

Abstract

The problem of face recognition using Laplacian pyramids with different orientations and independent components is addressed in this paper. The edginess like information is obtained by using Oriented Laplacian of Gaussian (OLOG) methods with four different orientations (0°, 45°, 90°, and 135°) then preprocessing is done by using Principle Component analysis (PCA) before obtaining the Independent Components. The independent components obtained by ICA algorithms are used as feature vectors for classification. The Euclidean distance (L2) classifier is used for testing of images. The algorithm is tested on two different databases of face images for variation in illumination, facial expressions and facial poses up to 180° rotation angle.

Keywords

Gaussian processes; face recognition; independent component analysis; principal component analysis; Euclidean distance classifier; ICA; Laplacian pyramids; PCA; face recognition; independent component analysis; oriented Laplacian of Gaussian; principle component analysis; Algorithm design and analysis; Face; Face recognition; Feature extraction; Image edge detection; Laplace equations; Principal component analysis; FastICA; Independent Component Analysis (ICA); Kernel ICA; Oriented Laplacian of Gaussian (OLOG); Principle Component analysis (PCA);

fLanguage

English

Publisher

ieee

Conference_Titel

Digital Information and Communication Technology and it's Applications (DICTAP), 2012 Second International Conference on

Conference_Location

Bangkok

Print_ISBN

978-1-4673-0733-8

Type

conf

DOI

10.1109/DICTAP.2012.6215338

Filename

6215338