Kooperativer Bibliotheksverbund

UID:

Umfang: 1 online resource (305 pages)

ISBN: 3-030-81982-5

Serie: Smart Sensors, Measurement and Instrumentation ; v.40

Anmerkung: Intro -- Preface -- Contents -- Part I Authentication Based on Measurements of Human Characteristics -- 1 Efficient Fingerprint Analysis Based on Sweat Pore Map -- 1.1 Introduction -- 1.2 Related Works -- 1.3 Proposed Approach -- 1.3.1 Step 1: Pores Detection -- 1.3.2 Step 2: Features Extraction -- 1.3.3 Step 3: Pores Alignment -- 1.3.4 Step 4: Pores Matching -- 1.4 Experiments and Performance Evaluation -- 1.4.1 Data Base -- 1.4.2 Training and Test Process -- 1.4.3 Feature Matching -- 1.4.4 Performance Evaluation -- 1.5 Conclusion -- References -- 2 Fingerprint Recognition Based on Level Three Features -- 2.1 Introduction -- 2.2 Biometry Background -- 2.2.1 Biometric Systems -- 2.2.2 Biology of the Fingerprint -- 2.3 Pores Detection -- 2.3.1 Related Works -- 2.3.2 Proposed Method -- 2.4 Pores Matching -- 2.4.1 Related Works -- 2.4.2 Proposed Method -- 2.5 Experimental Results -- 2.5.1 Database -- 2.5.2 Pores Detection -- 2.5.3 Recognition -- 2.6 Conclusion -- References -- 3 Fractal Analysis for Iris Multimodal Biometry -- 3.1 Introduction -- 3.2 Related Works -- 3.3 Feature Extraction Based on Fractal Analysis -- 3.4 Uni-Modal Recognition System -- 3.4.1 PBMLTiris Database Description -- 3.4.2 Pre-processing -- 3.4.3 Iris Segmentation (Daugman's Operator) -- 3.4.4 Normalization Based on the Pseudo-Polar Method (Masšek, ch3AmenispsbibspsMaek2003RecognitionOH) -- 3.4.5 Matching -- 3.5 Multi-modal Recognition System -- 3.5.1 Limitations of Uni-Modal Recognition System (Singh et al., ch3Amenispsbibspssingh2019comprehensive) -- 3.5.2 Fusion Sources -- 3.5.3 Fusion Levels -- 3.6 Experimental Results -- 3.6.1 Segmentation Results -- 3.6.2 Uni-Modal System Evaluation -- 3.6.3 Feature Level Fusion Results -- 3.6.4 Sensor Level Fusion Results -- 3.6.5 Score Level Fusion Results -- 3.7 Discussion and Conclusion -- References. , Part II Authentication by Biological Signals -- 4 Security with ECG Biometrics -- 4.1 Biometrics Definition -- 4.2 Biometrics with ECG -- 4.3 ECG Biometrics Approaches -- 4.3.1 Fiducial Approaches -- 4.3.2 Non-fiducial Approaches -- 4.4 ECG Signal Filters -- 4.5 ECG Biometric Classifiers -- 4.6 Evaluation of ECG Biometrics -- 4.7 Conclusion -- References -- 5 ECG Biometric System for Human Recognition Based on the Possibility Theory -- 5.1 Introduction -- 5.2 Possibility Theory -- 5.2.1 Possibility Distribution -- 5.2.2 Transformation from Probability Distribution to Possibility Distribution -- 5.3 Methodology -- 5.3.1 ECG Signal Pre-processing -- 5.3.2 Feature Extraction -- 5.3.3 Possibility Theory Based ECG Classification -- 5.3.4 Experimental Results and Discussion -- 5.4 Conclusion -- References -- 6 Surface EMG Based Biometric Person Authentication by a Grasshopper Optimized SVM Algorithm -- 6.1 Introduction -- 6.2 Biometry Based on sEMG Signals -- 6.3 Hybrid Grasshopper Optimization Algorithm and Support Vector Machine (GOA-SVM) -- 6.3.1 Grasshopper Optimization Algorithm (GOA) -- 6.3.2 GOA-SVM -- 6.4 Experimental Results -- 6.5 Conclusion -- References -- Part III Algorithm Based Methods of Multimodal Authentication -- 7 Tracklet and Signature Representation Using Part Appearance Mixture Approach in the Context of Multi-shot Person Re-Identification -- 7.1 Introduction -- 7.2 Main Challenges of Person Re-ID -- 7.3 Related Works -- 7.4 Person Re-ID Process -- 7.4.1 Detection -- 7.4.2 Multi-object Tracking -- 7.5 Part Appearance Mixture (PAM) Approach -- 7.5.1 Signature Representation -- 7.5.2 Similarity Metric for Signature Representation -- 7.5.3 Distance Computation Between Signatures -- 7.6 Experiments and Results -- 7.6.1 Datasets -- 7.6.2 Performance Evaluation -- 7.6.3 Evaluation of Signature Representation Quality -- 7.7 Conclusion. , References -- 8 A Novel Approach for Speaker Recognition in Degraded Conditions -- 8.1 Introduction -- 8.2 Related Works -- 8.3 Proposed Approach -- 8.3.1 Pre-processing -- 8.3.2 Feature Extraction -- 8.3.3 Classification -- 8.4 Experimental Results -- 8.5 Conclusion -- References -- 9 Visual Methods for Sign Language Recognition: A Modality-Based Review -- 9.1 Introduction -- 9.2 Human Actions Recognition Pipeline -- 9.3 Unimodal Methods -- 9.3.1 Recognition from Joint Streams -- 9.3.2 Recognition from RGB Streams -- 9.3.3 Recognition from Depth Streams -- 9.3.4 Unimodal Temporal Segmentation Approaches -- 9.4 Multi-modal Methods -- 9.4.1 Multi-modal Datasets for HAR -- 9.4.2 Multi-modal Fusion Approaches -- 9.4.3 Multi-modal Datasets for 3D FEs Recognition -- 9.4.4 Multi-modal Approaches for 3D FEs Recognition -- 9.5 Main Contributions Related to SL Recognition -- 9.5.1 SL Datasets -- 9.5.2 SL Visual-Recognition Based Works -- 9.6 Conclusion and Discussion -- 9.6.1 Datasets Level -- 9.6.2 Approaches Level -- 9.6.3 Commercial Solutions Level -- References -- 10 A Software Architecture for Developing Disease Registries -- 10.1 Introduction -- 10.2 Related Work -- 10.2.1 Technology -- 10.2.2 Data -- 10.2.3 Knowledge -- 10.2.4 Analytics -- 10.2.5 Services -- 10.2.6 Security -- 10.2.7 Sharing -- 10.3 Proposed Software Architecture -- 10.3.1 Technology Layer -- 10.3.2 Data Layer -- 10.3.3 Knowledge Layer -- 10.3.4 Analytics Layer -- 10.3.5 Service Layer -- 10.3.6 Security and Privacy -- 10.3.7 Sharing -- 10.3.8 Interactions -- 10.4 Use Cases -- 10.5 Conclusion -- References -- Part IV Biomedical Characteritics -- 11 3D Textures Analysis Based on Features Extraction -- 11.1 Introduction -- 11.2 Methods of Texture Measures -- 11.2.1 Decimal Descriptor Patterns (DDP) -- 11.2.2 Local Binary Patterns -- 11.2.3 Grey Level Co-occurrence Matrix Method. , 11.3 Experiments and Results -- 11.3.1 Databases -- 11.3.2 Phases of Simulation -- 11.3.3 3D MR Brain Images Analysis -- 11.3.4 3D Face Analysis -- 11.3.5 Discussion -- 11.4 Conclusion -- References -- 12 Image Processing and Analysis for Decision Making Applied to Melanoma -- 12.1 Introduction -- 12.2 About Melanoma -- 12.3 Diagnostic Aid System Based on Score Computation -- 12.3.1 Images Acquisition -- 12.3.2 Images Pretreatment -- 12.3.3 Lesion Detection -- 12.3.4 Interpretation of Medical Images -- 12.4 Diagnostic Aid System Based on Machine Learning -- 12.4.1 Images Acquisition -- 12.4.2 Pretreatment of Dermatoscopic Images -- 12.4.3 Segmentation of Lesion Based on Region Growing Method -- 12.4.4 Skin Lesion Analysis -- 12.5 Experimental Results and Discussion -- 12.5.1 Approach Based on the MultiOtsu Principle -- 12.5.2 Approach Based on the Region Growing Method -- 12.5.3 Evaluation and Discussion -- 12.6 Conclusion -- References -- 13 Biomedical Computer Aided Design Systems: Application to Alzheimer Disease -- 13.1 Introduction -- 13.2 Proposed Methodology -- 13.3 Previous Works -- 13.3.1 Partial Least Square (PLS) -- 13.3.2 Kernel Partial Least Square (KPLS) -- 13.4 Proposed Downsized KPLS Method (DPLS) -- 13.5 Optimization with Multi-objective Optimization Algorithm -- 13.5.1 Principle -- 13.5.2 Selection of Kernel Parameter with Multi-Objective Optimization Algorithm -- 13.6 Classification Using Neural Networks -- 13.7 Experiments -- 13.7.1 Experiments on ADNI Dataset -- 13.7.2 Experiments on OASIS Dataset -- 13.8 Conclusion and Future Work -- References.

Weitere Ausg.: ISBN 3-030-81981-7

Sprache: Englisch

URL: lizenzpflichtig

UID:

Umfang: 1 online resource (305 pages)

ISBN: 3-030-81982-5

Serie: Smart Sensors, Measurement and Instrumentation ; v.40

Anmerkung: Intro -- Preface -- Contents -- Part I Authentication Based on Measurements of Human Characteristics -- 1 Efficient Fingerprint Analysis Based on Sweat Pore Map -- 1.1 Introduction -- 1.2 Related Works -- 1.3 Proposed Approach -- 1.3.1 Step 1: Pores Detection -- 1.3.2 Step 2: Features Extraction -- 1.3.3 Step 3: Pores Alignment -- 1.3.4 Step 4: Pores Matching -- 1.4 Experiments and Performance Evaluation -- 1.4.1 Data Base -- 1.4.2 Training and Test Process -- 1.4.3 Feature Matching -- 1.4.4 Performance Evaluation -- 1.5 Conclusion -- References -- 2 Fingerprint Recognition Based on Level Three Features -- 2.1 Introduction -- 2.2 Biometry Background -- 2.2.1 Biometric Systems -- 2.2.2 Biology of the Fingerprint -- 2.3 Pores Detection -- 2.3.1 Related Works -- 2.3.2 Proposed Method -- 2.4 Pores Matching -- 2.4.1 Related Works -- 2.4.2 Proposed Method -- 2.5 Experimental Results -- 2.5.1 Database -- 2.5.2 Pores Detection -- 2.5.3 Recognition -- 2.6 Conclusion -- References -- 3 Fractal Analysis for Iris Multimodal Biometry -- 3.1 Introduction -- 3.2 Related Works -- 3.3 Feature Extraction Based on Fractal Analysis -- 3.4 Uni-Modal Recognition System -- 3.4.1 PBMLTiris Database Description -- 3.4.2 Pre-processing -- 3.4.3 Iris Segmentation (Daugman's Operator) -- 3.4.4 Normalization Based on the Pseudo-Polar Method (Masšek, ch3AmenispsbibspsMaek2003RecognitionOH) -- 3.4.5 Matching -- 3.5 Multi-modal Recognition System -- 3.5.1 Limitations of Uni-Modal Recognition System (Singh et al., ch3Amenispsbibspssingh2019comprehensive) -- 3.5.2 Fusion Sources -- 3.5.3 Fusion Levels -- 3.6 Experimental Results -- 3.6.1 Segmentation Results -- 3.6.2 Uni-Modal System Evaluation -- 3.6.3 Feature Level Fusion Results -- 3.6.4 Sensor Level Fusion Results -- 3.6.5 Score Level Fusion Results -- 3.7 Discussion and Conclusion -- References. , Part II Authentication by Biological Signals -- 4 Security with ECG Biometrics -- 4.1 Biometrics Definition -- 4.2 Biometrics with ECG -- 4.3 ECG Biometrics Approaches -- 4.3.1 Fiducial Approaches -- 4.3.2 Non-fiducial Approaches -- 4.4 ECG Signal Filters -- 4.5 ECG Biometric Classifiers -- 4.6 Evaluation of ECG Biometrics -- 4.7 Conclusion -- References -- 5 ECG Biometric System for Human Recognition Based on the Possibility Theory -- 5.1 Introduction -- 5.2 Possibility Theory -- 5.2.1 Possibility Distribution -- 5.2.2 Transformation from Probability Distribution to Possibility Distribution -- 5.3 Methodology -- 5.3.1 ECG Signal Pre-processing -- 5.3.2 Feature Extraction -- 5.3.3 Possibility Theory Based ECG Classification -- 5.3.4 Experimental Results and Discussion -- 5.4 Conclusion -- References -- 6 Surface EMG Based Biometric Person Authentication by a Grasshopper Optimized SVM Algorithm -- 6.1 Introduction -- 6.2 Biometry Based on sEMG Signals -- 6.3 Hybrid Grasshopper Optimization Algorithm and Support Vector Machine (GOA-SVM) -- 6.3.1 Grasshopper Optimization Algorithm (GOA) -- 6.3.2 GOA-SVM -- 6.4 Experimental Results -- 6.5 Conclusion -- References -- Part III Algorithm Based Methods of Multimodal Authentication -- 7 Tracklet and Signature Representation Using Part Appearance Mixture Approach in the Context of Multi-shot Person Re-Identification -- 7.1 Introduction -- 7.2 Main Challenges of Person Re-ID -- 7.3 Related Works -- 7.4 Person Re-ID Process -- 7.4.1 Detection -- 7.4.2 Multi-object Tracking -- 7.5 Part Appearance Mixture (PAM) Approach -- 7.5.1 Signature Representation -- 7.5.2 Similarity Metric for Signature Representation -- 7.5.3 Distance Computation Between Signatures -- 7.6 Experiments and Results -- 7.6.1 Datasets -- 7.6.2 Performance Evaluation -- 7.6.3 Evaluation of Signature Representation Quality -- 7.7 Conclusion. , References -- 8 A Novel Approach for Speaker Recognition in Degraded Conditions -- 8.1 Introduction -- 8.2 Related Works -- 8.3 Proposed Approach -- 8.3.1 Pre-processing -- 8.3.2 Feature Extraction -- 8.3.3 Classification -- 8.4 Experimental Results -- 8.5 Conclusion -- References -- 9 Visual Methods for Sign Language Recognition: A Modality-Based Review -- 9.1 Introduction -- 9.2 Human Actions Recognition Pipeline -- 9.3 Unimodal Methods -- 9.3.1 Recognition from Joint Streams -- 9.3.2 Recognition from RGB Streams -- 9.3.3 Recognition from Depth Streams -- 9.3.4 Unimodal Temporal Segmentation Approaches -- 9.4 Multi-modal Methods -- 9.4.1 Multi-modal Datasets for HAR -- 9.4.2 Multi-modal Fusion Approaches -- 9.4.3 Multi-modal Datasets for 3D FEs Recognition -- 9.4.4 Multi-modal Approaches for 3D FEs Recognition -- 9.5 Main Contributions Related to SL Recognition -- 9.5.1 SL Datasets -- 9.5.2 SL Visual-Recognition Based Works -- 9.6 Conclusion and Discussion -- 9.6.1 Datasets Level -- 9.6.2 Approaches Level -- 9.6.3 Commercial Solutions Level -- References -- 10 A Software Architecture for Developing Disease Registries -- 10.1 Introduction -- 10.2 Related Work -- 10.2.1 Technology -- 10.2.2 Data -- 10.2.3 Knowledge -- 10.2.4 Analytics -- 10.2.5 Services -- 10.2.6 Security -- 10.2.7 Sharing -- 10.3 Proposed Software Architecture -- 10.3.1 Technology Layer -- 10.3.2 Data Layer -- 10.3.3 Knowledge Layer -- 10.3.4 Analytics Layer -- 10.3.5 Service Layer -- 10.3.6 Security and Privacy -- 10.3.7 Sharing -- 10.3.8 Interactions -- 10.4 Use Cases -- 10.5 Conclusion -- References -- Part IV Biomedical Characteritics -- 11 3D Textures Analysis Based on Features Extraction -- 11.1 Introduction -- 11.2 Methods of Texture Measures -- 11.2.1 Decimal Descriptor Patterns (DDP) -- 11.2.2 Local Binary Patterns -- 11.2.3 Grey Level Co-occurrence Matrix Method. , 11.3 Experiments and Results -- 11.3.1 Databases -- 11.3.2 Phases of Simulation -- 11.3.3 3D MR Brain Images Analysis -- 11.3.4 3D Face Analysis -- 11.3.5 Discussion -- 11.4 Conclusion -- References -- 12 Image Processing and Analysis for Decision Making Applied to Melanoma -- 12.1 Introduction -- 12.2 About Melanoma -- 12.3 Diagnostic Aid System Based on Score Computation -- 12.3.1 Images Acquisition -- 12.3.2 Images Pretreatment -- 12.3.3 Lesion Detection -- 12.3.4 Interpretation of Medical Images -- 12.4 Diagnostic Aid System Based on Machine Learning -- 12.4.1 Images Acquisition -- 12.4.2 Pretreatment of Dermatoscopic Images -- 12.4.3 Segmentation of Lesion Based on Region Growing Method -- 12.4.4 Skin Lesion Analysis -- 12.5 Experimental Results and Discussion -- 12.5.1 Approach Based on the MultiOtsu Principle -- 12.5.2 Approach Based on the Region Growing Method -- 12.5.3 Evaluation and Discussion -- 12.6 Conclusion -- References -- 13 Biomedical Computer Aided Design Systems: Application to Alzheimer Disease -- 13.1 Introduction -- 13.2 Proposed Methodology -- 13.3 Previous Works -- 13.3.1 Partial Least Square (PLS) -- 13.3.2 Kernel Partial Least Square (KPLS) -- 13.4 Proposed Downsized KPLS Method (DPLS) -- 13.5 Optimization with Multi-objective Optimization Algorithm -- 13.5.1 Principle -- 13.5.2 Selection of Kernel Parameter with Multi-Objective Optimization Algorithm -- 13.6 Classification Using Neural Networks -- 13.7 Experiments -- 13.7.1 Experiments on ADNI Dataset -- 13.7.2 Experiments on OASIS Dataset -- 13.8 Conclusion and Future Work -- References.

Weitere Ausg.: ISBN 3-030-81981-7

Sprache: Englisch

UID:

Umfang: X, 303 p. 169 illus., 137 illus. in color. , online resource.

Ausgabe: 1st ed. 2021.

ISBN: 9783030819828

Serie: Smart Sensors, Measurement and Instrumentation, 40

Inhalt: The book highlights recent developments in human biometrics, covering a wide range of methods based on biological signals, image processing, and measurements of human characteristics such as fingerprints and iris or medical characteristics. Human Biometrics is becoming increasingly crucial in forensics security and medicine. They provide a solid basis for identifying individuals based on unique physical characteristics or diseases based on characteristic biomedical measurements. As such, the book offers an essential reference guide about biometry methods for students, engineers, designers, and technicians. .

Anmerkung: Ecient Fingerprint Analysis based on Sweat Pore Map -- Fingerprint Recognition based on Level Three Features -- Fractal Analysis for Iris Multimodal Biometry -- Security with ECG Biometrics -- ECG Biometric System for Human Recognition based on the Possibility Theory -- Surface EMG based Biometric Person Authentication by a Grasshopper Optimized SVM Algorithm -- Tracklet and Signature Representation using Part Appearance Mixture Approach in the Context of Multi-Shot Person Re-Identification -- A Novel Approach for Speaker Recognition in Degraded Conditions -- Visual Methods for Sign Language Recognition: A Modality-Based Review -- A Software Architecture for Developing Disease Registries -- 3D Textures Analysis based on Features Extraction -- Image Processing and Analysis for Decision Making Applied to Melanoma -- Biomedical Computer Aided Design Systems: Application to Alzheimer Disease.

In: Springer Nature eBook

Weitere Ausg.: Printed edition: ISBN 9783030819811

Weitere Ausg.: Printed edition: ISBN 9783030819835

Weitere Ausg.: Printed edition: ISBN 9783030819842

Sprache: Englisch

DOI: 10.1007/978-3-030-81982-8

URL: https://doi.org/10.1007/978-3-030-81982-8