Hierarchical Fusion of Multi Spectral Face Images for Improved ... - IIIT

MSF⎪⎧MS= ⎨⎪⎩ MSIFIFMS+ 1F =ififMSmIFCDCDiFiF≥ T< TIFIF(22)3.2. Fusion of Features from Multi Spectral Face ImagesTo enhance the performance of face recognition, the amplitude and phase features of faceimages from different spectrum are fused as shown in Fig. 3. Features are extracted fromtwo single-spectrum face images using the algorithm described in Section 2. For eachimage, the extracted amplitude and phase features are fused using the algorithm describedin Section 3.1 to generate two fused feature vectorsFF V andFF IR in visible andinfrared spectrum respectively. These fused feature vectors are then combined usingEquation 25, to generate an optimal fused feature vector, FF − ,VIR⎧FA−V, if O1(x,y)> 0FFV = ⎨⎩FP−V, if O1( x,y)< 0(23)⎧FA−IR,if O2( x,y)> 0FFIR = ⎨⎩FP−IR,if O2( x,y)< 0(24)⎧ FFV, if O3( x,y)> 0FFV −IR= ⎨⎩FFIR,if O3(x,y)< 0(25)where O x,y),O ( x,) and O ( x,) are the outputs of the three trained 2υ -SVM. These1( 2 y3 yfeature vectors are further matched using the correlation based matching described in14