Intelligent Wavelet Based Techniques for Advanced Multimedia Applications

✍ Scribed by Rajiv Singh, Swati Nigam, Amit Kumar Singh, Mohamed Elhoseny

• Publisher: Springer
• Year: 2020
• Tongue: English
• Leaves: 158
• Category: Library

✦ Synopsis

This book contains high-quality research articles and reviews that promote research and reflect the most recent advances in intelligent wavelet based techniques for advanced multimedia applications as well as other emerging areas. In recent time, wavelet transforms have become useful in many signal, image and video processing applications, especially for multimedia security and surveillance. A few applications of wavelets in security and surveillance are watermarking, fusion, steganography, object detection, tracking, motion recognition and intention recognition, etc. Wavelets are well capable of analyzing signal, image and video at different resolution levels, popularly known as multiresolution analysis. The multiresolution analysis is advantageous in multimedia security and surveillance applications. It provides flexibility in selection of different resolution levels that leads to better accuracy. Furthermore, recently sparse representation has become an advancement to analyze wavelet coefficients. It is observed that wavelet transforms possess the invariance property which makes them suitable for many vision applications.

This book provides a concise overview of the current state of the art and disseminates some of the novel and exciting ideas and techniques. In addition, it is also helpful for the senior undergraduate and graduate students, researcher, academicians, IT professional and providers, citizens, customers as well as policy makers working in this area as well as other emerging applications demanding state-of-the-art wavelet based multimedia applications.

✦ Table of Contents

Foreword
Preface
Outline of the Book and Chapter Synopsis
Special Acknowledgments
Contents
About the Authors
List of Figures
List of Tables
Chapter 1: Wavelets and Intelligent Multimedia Applications: An Introduction
1.1 Introduction
1.2 Motivations and Objectives
1.3 Wavelet Transforms and Intelligent Multimedia Applications
1.3.1 Image Fusion
1.3.2 Image Watermarking
1.3.3 Video Watermarking
1.3.4 Object Tracking
1.3.5 Person Identification
1.3.6 Activity Recognition
1.3.7 Emotion Recognition Using Facial Expressions
1.4 Summary
References
Chapter 2: Wavelet Transforms: From Classical to New Generation Wavelets
2.1 Introduction
2.2 Wavelet Transforms
2.2.1 Discrete Wavelet Transform
2.2.2 Complex Wavelet Transforms
2.2.2.1 Dual Tree Complex Wavelet Transform (DTCWT)
2.2.2.2 Discrete Complex Wavelet Transform (DCxWT)
2.2.2.3 Properties of Complex Wavelet Transforms
2.2.3 Curvelet Transform
2.2.3.1 Analysis
2.2.3.2 Synthesis
2.2.4 Contourlet Transform
2.2.5 Nonsubsampled Contourlet Transform
2.3 Summary
References
Chapter 3: An Overview of Medical Image Fusion in Complex Wavelet Domain
3.1 Introduction
3.2 Background and Literature
3.3 Methodology and Experiments
3.4 Fusion Results and Discussions
3.4.1 Qualitative Evaluation
3.4.2 Quantitative Evaluation
3.5 Summary
References
Chapter 4: Integration of Wavelet Transforms for Single and Multiple Image Watermarking
4.1 Introduction
4.2 Related Work
4.3 Theoretical Background
4.3.1 Nonsubsampled Contourlet Transform (NSCT)
4.3.2 Discrete Cosine Transform (DCT)
4.3.3 Multiresolution Singular Value Decomposition (MSVD)
4.3.4 Arnold Transform
4.4 Methodology and Comparative Analysis
4.5 Summary
References
Chapter 5: On Wavelet Domain Video Watermarking Techniques
5.1 Introduction
5.2 Video Watermarking: An Overview of Applications and Characteristics
5.3 Video Watermarking in Wavelet Domain: Literature Review
5.4 Methodology and Evaluation Strategies
5.5 Summary
References
Chapter 6: Object Tracking
6.1 Introduction
6.2 Literature Analysis
6.2.1 Sensors Based Systems
6.2.2 Marker Based Vision Systems
6.2.3 Marker-Less Vision Systems
6.2.4 Robot-Guided Systems
6.3 Significance of Curvelet in Tracking
6.4 Experimentation and Results
6.4.1 Single Object Tracking: Child Video Results
6.4.2 Multiple Object Tracking: Soccer Video Results
6.4.3 Multiple Object Tracking: Own Video Results
6.4.4 Multiple Object Tracking: Challenge Video Results
6.4.5 Performance Evaluation
6.5 Summary
References
Chapter 7: Camouflaged Person Identification
7.1 Introduction
7.2 Wavelet for Person Identification
7.3 A General Algorithm
7.3.1 Representation of Camouflaged Person Objects in Real Scenarios
7.3.2 Two Step Preprocessing of Images
7.3.3 Extraction of Multi-Resolution Wavelet Coefficients
7.3.4 Wavelet Coefficients Classification
7.4 Results and Discussion
7.5 Summary
References
Chapter 8: Wavelets for Activity Recognition
8.1 Introduction
8.2 Literature Review
8.3 Activity Framework
8.3.1 Input Video
8.3.2 Preprocessing
8.3.3 Motion Segmentation
8.3.4 Wavelet Feature Extraction
8.3.5 Classifier Training and Testing
8.4 Results and Discussion
8.4.1 Results over Weizmann Dataset
8.4.2 Results over KTH Dataset
8.5 Summary
References
Chapter 9: Biometric Recognition of Emotions Using Wavelets
9.1 Introduction
9.2 Literature Review
9.2.1 Basic FER Techniques
9.2.2 Micro FER Techniques
9.2.3 3D FER Techniques
9.3 FER Framework
9.3.1 Face Detection and Normalization
9.3.2 Discrete Wavelet Coefficient Extraction
9.3.3 Feature Selection
9.3.4 Multiclass SVM Classifier
9.4 Results and Discussion
9.4.1 Experiments over the JAFFE Dataset
9.4.2 Extended Cohn-Kanade (CK+) Dataset Results
9.5 Summary
References
Chapter 10: Intelligent Multimedia Applications in Wavelet Domain: New Trends and Future Research Directions
10.1 Introduction
10.2 Video Analytics in Wavelet Domain
10.2.1 Single and Multiple Object Tracking
10.2.2 Person Identification and Re-Identification
10.2.3 Abnormal Activity Recognition
10.2.4 Emotion Recognition
10.2.5 Crowd Behavior Analysis
10.3 Wavelets and Deep Learning
10.4 Wavelets for Healthcare Monitoring
10.5 Wavelets for Internet of Things
10.6 Wavelets in Biology and Agriculture
10.7 Summary
References