JOURNAL OF COMPUTERS (JCP)
ISSN : 1796-203X
Volume : 2 Issue : 4 Date : June 2007
Rule Based Segmentation and Subject Identification Using Fiducial Features and Subspace
Erhan AliRiza Ince and Syed Amjad Ali
Full Text: PDF (562 KB)
This paper describes a framework for carrying out face recognition on a subset of standard color
FERET database using two different subspace projection methods, namely PCA and Fisherfaces.
At first, a rule based skin region segmentation algorithm is discussed and then details about eye
localization and geometric normalization are given. The work achieves scale and rotation invariance
by fixing the inter ocular distance to a selected value and by setting the direction of the eye-to-eye
axis. Furthermore, the work also tries to avoid the small sample space (S3) problem by increasing
the number of shots per subject through the use of one duplicate set per subject. Finally,
performance analysis for the normalized global faces, the individual extracted features and for a
multiple component combination are provided using a nearest neighbour classifier with Euclidean
and/or Cosine distance metrics.
Skin color segmentation, color FERET database, geometric normalization, feature extraction,
subspace analysis methods.