Master Thesis - Department of Computer Science

of the five subspace methods on them. During the identification phase, we create all
subject-specific subband faces T(li, ki), i = 1, 2, ...., C for the test image, T . Then the
C different subband faces are projected onto the corresponding subspaces to obtain
the distances from C different classes. More specifically, i th test subband face T(li, ki) is
projected on i th subspace LSAi to obtain the (Euclidean) distance of the test sample
from i th class. A process of normalization (using min-max, with score value in range
[0, 1]) is performed separately on each subspace to compare the C different distances
computed in C different subspaces for obtaining the class label based on minimum
or maximum membership rule. Let D = [d1, . . . , di, . . . , dC] be the vector of distance
values obtained from C different subspaces after normalization. Now the class label
for test sample T , L(T ), is obtained by using minimum membership rule on D.
L(T ) = arg min
c dc. (3.11)
The method for verification is simpler than the identification stage as we claim a
person’s identity and allow the system to verify it. Only one subband face T(lc, kc) is
generated for the test sample T , where the claimed identity is class c. Then T(lc, kc) is
projected on the c th subspace LSAc to obtain the distance measure from c th class. The
calculated distance measure is checked against a predefined threshold value to produce
the output as acceptance or rejection. In the next section, we provide experimental
results for our proposed method and also compare our method with the approach of
Ekenel’s multiresolution face recognition [36] (the closest and recent competitor of
our approach).
3.4 Experimental Results
3.4.1 Databases Used
In this chapter, three face databases were used for experiments - Yale, PIE and ORL,
where:
• The Yale face database has 15 subjects with 11 samples each, having variations
in expression and illumination for each subject.
• A subset of the PIE (Pose Illumination and Expression) face database [112, 5]
with 60 subjects, where only the frontal poses (camera: c27) were used. For
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