TITLE:
Study of Similarity Measures with Linear Discriminant Analysis for Face Recognition
AUTHORS:
Mohamed A. El-Sayed, Kadry Hamed
KEYWORDS:
Fuzzy Sets, Similarity Measure, Distance Measure, LDA, Face Recognition
JOURNAL NAME:
Journal of Software Engineering and Applications,
Vol.8 No.9,
September
16,
2015
ABSTRACT: Face recognition systems have been in the
active research in the area of image processing for quite a long time.
Evaluating the face recognition system was carried out with various types of
algorithms used for extracting the features, their classification and matching.
Similarity measure or distance measure is also an important factor in assessing
the quality of a face recognition system. There are various distance measures
in literature which are widely used in this area. In this work, a new class of
similarity measure based on the Lp metric between fuzzy sets is proposed which
gives better results when compared to the existing distance measures in the
area with Linear Discriminant Analysis (LDA). The result points to a positive
direction that with the existing feature extraction methods itself the results
can be improved if the similarity measure in the matching part is efficient.