Class Specific Threshold Selection in Face Space Using Set Estimation Technique for RGB Color Components

  • Madhura Datta
  • C. A. Murthy
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5909)


In conventional face recognition techniques, any query image is always classified to one of the face classes irrespective of whether the query image is a face or not. Most of the recognition algorithms are dissimilarity based, and one needs to put a proper threshold on the dissimilarity value for the sake of classification. In this paper, we have introduced a novel thresholding technique for classification, where the query image is not necessarily classified to one of the classes in the training set. The theoretical formulation of the thresholding technique and its utility are demonstrated on color face and non face datasets with RGB color components as features in the subspace. The proposed threshold selection is based on statistical method of set estimation and is guided by minimal spanning tree. Experiment shows that the proposed class specific threshold based technique performs better than the non threshold based systems using subspace algorithms.


Feature extraction Color components Minimal spanning tree Intra-class threshold Set estimation 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Madhura Datta
    • 1
  • C. A. Murthy
    • 2
  1. 1.UGC-Academic Staff CollegeUniversity of CalcuttaKolkataIndia
  2. 2.Machine Intelligence UnitIndian Statistical InstituteKolkataIndia

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