Master Thesis - Department of Computer Science
Master Thesis - Department of Computer Science
Master Thesis - Department of Computer Science
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3 An Efficient Method <strong>of</strong> Face Recognition using Subject-Specific Sub-<br />
band Faces 44<br />
3.1 Introduction and Motivation . . . . . . . . . . . . . . . . . . . . . . . 45<br />
3.2 Subband Face Representation . . . . . . . . . . . . . . . . . . . . . . 48<br />
3.2.1 Wavelet Decomposition . . . . . . . . . . . . . . . . . . . . . 48<br />
3.2.2 Subband Face Reconstruction . . . . . . . . . . . . . . . . . . 49<br />
3.3 Proposed Methods for Subject-Specific Subband Selection . . . . . . . 53<br />
3.3.1 Criteria used for measuring Goatishness and Lambishness . . . 55<br />
3.3.2 Subject-Specific Subband Selection Algorithm . . . . . . . . . 57<br />
3.4 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . . 60<br />
3.4.1 Databases Used . . . . . . . . . . . . . . . . . . . . . . . . . . 60<br />
3.4.2 Performance Analysis on Three Standard Face Databases . . . 61<br />
3.4.3 Comparison with Ekenel’s Multiresolution Face Recognition [36] 64<br />
3.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69<br />
4 Dual Space Face Recognition using Feature and Decision Fusion 70<br />
4.1 Subspace Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71<br />
4.2 Obtaining Eigenmodels in Range Space and Null Space <strong>of</strong> Within-class<br />
Scatter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74<br />
4.3 Feature Fusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77<br />
4.3.1 Techniques for Merging Eigenmodels . . . . . . . . . . . . . . 77<br />
4.3.2 Search Criterion and Techniques for Optimal Feature Selection 79<br />
4.3.3 Algorithm for Feature Fusion . . . . . . . . . . . . . . . . . . 81<br />
4.4 Decision Fusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83<br />
4.4.1 Existing Techniques for Decision Fusion . . . . . . . . . . . . 83<br />
4.4.2 Proposed Technique for Decision Fusion . . . . . . . . . . . . 84<br />
4.4.3 Algorithm for Decision Fusion . . . . . . . . . . . . . . . . . . 90<br />
4.5 Experimental Results and Discussion . . . . . . . . . . . . . . . . . . 91<br />
4.5.1 Effect <strong>of</strong> Number <strong>of</strong> Training Samples on the Performance <strong>of</strong><br />
Null Space and Range Space . . . . . . . . . . . . . . . . . . . 92<br />
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