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Record Nr. |
UNINA9910964750803321 |
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Titolo |
Face recognition : methods, applications and technology / / Adamo Quaglia and Calogera M. Epifano, editors |
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Pubbl/distr/stampa |
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New York, : Nova Science, c2012 |
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ISBN |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (252 p.) |
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Collana |
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Computer Science, Technology and Applications |
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Altri autori (Persone) |
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QuagliaAdamo |
EpifanoCalogera M |
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Disciplina |
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Soggetti |
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Human face recognition (Computer science) |
Optical character recognition |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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""FACE RECOGNITION METHODS, APPLICATIONS AND TECHNOLOGY ""; ""FACE RECOGNITION METHODS, APPLICATIONS AND TECHNOLOGY ""; ""CONTENTS ""; ""PREFACE ""; ""ACCURACY OF FACE RECOGNITION""; ""ABSTRACT ""; ""INTRODUCTION ""; ""FAMILIAR VERSUS UNFAMILIAR FACE PROCESSING ""; ""ACCURACY OF UNFAMILIAR FACE MEMORY ""; ""RECOGNITION MEMORY ""; ""EYE-WITNESS MEMORY""; ""IMMEDIATE MEMORY ""; ""CHANGE BLINDNESS ""; ""ACCURACY OF UNFAMILIAR FACE PERCEPTION ""; ""INDIVIDUAL DIFFERENCES IN UNFAMILIAR FACE RECOGNITION""; ""ACCURACY OF FAMILIAR FACE RECOGNITION""; ""CONCLUSION ""; ""REFERENCES "" |
""EXTENDED 2-D PCA FOR FACE RECOGNITION: ANALYSIS, ALGORITHMS, AND PERFORMANCE ENHANCEMENT """"ABSTRACT ""; ""1. INTRODUCTION""; ""2. AN OVERVIEW OF PCA AND 2-D PCA METHODS ""; ""2.1. PCA ""; ""2.2. Two-Dimensional PCA ""; ""3. AN EXTENDED 2-D PCA TECHNIQUE FOR FACE RECOGNITION""; ""3.1. A Closer Look at 2-D PCA � a Row Oriented Processing Technique ""; ""3.2. A Column Oriented 2-D PCA ""; ""3.3. An Extended 2-D PCA (E-2DPCA) Technique ""; ""3.4. Classification Measures ""; ""4. PRE-PROCESSING TECHNIQUES FOR PERFORMANCE ENHANCEMENT""; ""4.1. Perfect Histogram Matching (PHM)"" |
""4.2. De-Noising of Face Images by DWT and TV Minimization """"4.3. Dealing with Face Occlusions ""; ""4.4. An Enhanced Face Recognition |
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System""; ""5. EXPERIMENTAL RESULTS ""; ""5.1. The Databases ""; ""5.2. Experimental Results of E-2DPCA � a Case Study ""; ""5.3. Additional Results for PCA, 2DPCA and E-2DPCA ""; ""5.4. Performance of an Enhanced Face Recognition System ""; ""5.5. Robustness of the Enhanced Face Recognition System to Noise and Face Occlusions""; ""CONCLUSION ""; ""REFERENCES "" |
""FACE RECOGNITION BASED ON COMPOSITE CORRELATION FILTERS: ANALYSIS OF THEIR PERFORMANCES """"ABSTRACT ""; ""1. INTRODUCTION ""; ""2. SOME PRELIMINARY CONSIDERATIONS AND RELATION TO PREVIOUS WORK ""; ""3. A BRIEF OVERVIEW OF CORRELATION FILTERS ""; ""3.1. Adapted Filter (Ad) ""; ""3.2. Phase-Only Filter (POF) ""; ""3.3. Binary Phase-Only Filter (BPOF) ""; ""3.4. Inverse Filter (IF) ""; ""3.5. Compromise Optimal Filter (OT) ""; ""3.6. Classical Composite Filter (COMP) ""; ""3.7. Segmented Composite Filter (SPOF) ""; ""3.8. Minimum Average Correlation Energy (MACE) "" |
""3.9. Amplitude-Modulated Phase-Only Filter (AMPOF) """"3.10. Optimal Trade-off MACH (OT MACH) ""; ""3.11. Asymmetric Segmented Phase Only Filter (ASPOF) ""; ""4. COMPARATIVE STUDY OF COMPOSITE CORRELATIONS FILTERS WITH BINARY IMAGES""; ""4.1. Adapted Composite Filter ""; ""4.2. Composite POF ""; ""4.3. Composite Binary POF""; ""4.4. Inverse Composite Filter ""; ""4.5. Robustness against Noise ""; ""4.6. Optimized Composite Filters ""; ""CONCLUSION ""; ""ACKNOWLEDGMENTS ""; ""REFERENCES ""; ""FACE RECOGNITION EMPLOYING PCA BASED ARTIFICIAL IMMUNE NETWORKS ""; ""ABSTRACT "" |
""INTRODUCTION "" |
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Sommario/riassunto |
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Face recognition has been an active area of research in image processing and computer vision due to its extensive range of prospective applications relating to biometrics, information security, video surveillance, law enforcement, identity authentication, smart cards, and access control systems. Topics discussed in this compilation include two-dimensional principal component analysis algorithms for face recognition; principal component analysis (PCA) and artificial immune networks in face recognition; multi-class learning facial age estimation and forensic face recognition. |
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