¹Department of Electrical and Electronic Engineering, Eastern Mediterranean University, North Cyprus
²Department of Computer Technology and Information Systems, Bilkent University, Turkey

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Abstract—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.

Index Terms—Skin color segmentation, color FERET database, geometric normalization, feature extraction, subspace analysis methods

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Cite: Erhan AliRiza ˙Ince, Syed Amjad Ali, "Rule Based Segmentation and Subject Identification Using Fiducial Features and Subspace Projection Methods," Journal of Computers vol. 2, no. 4, pp. 68-75, 2007.