Fundamentals of Image, Audio, and Video Processing Using MATLAB : With Applications to Pattern Recognition.

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This book introduces the concepts and principles of media processing and its applications in pattern recognition by adopting a hands-on approach using program implementations. The book covers the tools and techniques for reading, modifying and writing image, audio and video files using the data anal...

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Bibliographic Details
Main Author: Parekh, Ranjan
Format: e-Book
Language:English
Published: Milton : Taylor & Francis Group, 2021.
Edition:1st ed.
Subjects:
MATLAB.
Digital video.
Image processing-Digital techniques.
Electronic books.
Online Access:Full-text access
Table of Contents:
  • Cover
  • Half Title
  • Title Page
  • Copyright Page
  • Table of Contents
  • Preface
  • Author
  • Abbreviations
  • 1 Image Processing
  • 1.1 Introduction
  • 1.2 Toolboxes and Functions
  • 1.2.1 Basic MATLAB (BM) Functions
  • 1.2.2 Image Processing Toolbox (IPT) Functions
  • 1.2.3 Signal Processing Toolbox (SPT) Functions
  • 1.2.4 Wavelet Toolbox (WT) Functions
  • 1.3 Import Export and Conversions
  • 1.3.1 Read and Write Image Data
  • 1.3.2 Image-Type Conversion
  • 1.3.3 Image Color
  • 1.3.4 Synthetic Images
  • 1.4 Display and Exploration
  • 1.4.1 Basic Display
  • 1.4.2 Interactive Exploration
  • 1.4.3 Building Interactive Tools
  • 1.5 Geometric Transformation and Image Registration
  • 1.5.1 Common Geometric Transformations
  • 1.5.2 Affine and Projective Transformations
  • 1.5.3 Image Registration
  • 1.6 Image Filtering and Enhancement
  • 1.6.1 Image Filtering
  • 1.6.2 Edge Detection
  • 1.6.3 Contrast Adjustment
  • 1.6.4 Morphological Operations
  • 1.6.5 ROI and Block Processing
  • 1.6.6 Image Arithmetic
  • 1.6.7 De-blurring
  • 1.7 Image Segmentation and Analysis
  • 1.7.1 Image Segmentation
  • 1.7.2 Object Analysis
  • 1.7.3 Region and Image Properties
  • 1.7.4 Texture Analysis
  • 1.7.5 Image Quality
  • 1.7.6 Image Transforms
  • 1.8 Working in Frequency Domain
  • 1.9 Image Processing Using Simulink
  • 1.10 Notes on 2-D Plotting Functions
  • 1.11 Notes on 3-D Plotting Functions
  • Review Questions
  • 2 Audio Processing
  • 2.1 Introduction
  • 2.2 Toolboxes and Functions
  • 2.2.1 Basic MATLAB (BM) Functions
  • 2.2.2 Audio System Toolbox (AST) Functions
  • 2.2.3 DSP System Toolbox (DSPST) Functions
  • 2.2.4 Signal Processing Toolbox (SPT) Functions
  • 2.3 Sound Waves
  • 2.4 Audio I/O and Waveform Generation
  • 2.5 Audio Processing Algorithm Design
  • 2.6 Measurements and Feature Extraction
  • 2.7 Simulation, Tuning and Visualization.
  • 2.8 Musical Instrument Digital Interface (MIDI)
  • 2.9 Temporal Filters
  • 2.10 Spectral Filters
  • 2.11 Audio Processing Using Simulink
  • Review Questions
  • 3 Video Processing
  • 3.1 Introduction
  • 3.2 Toolboxes and Functions
  • 3.2.1 Basic MATLAB (BM) Functions
  • 3.2.2 Computer Vision System Toolbox (CVST) Functions
  • 3.3 Video Input Output and Playback
  • 3.4 Processing Video Frames
  • 3.5 Video Color Spaces
  • 3.6 Object Detection
  • 3.6.1 Blob Detector
  • 3.6.2 Foreground Detector
  • 3.6.3 People Detector
  • 3.6.4 Face Detector
  • 3.6.5 Optical Character Recognition (OCR)
  • 3.7 Motion Tracking
  • 3.7.1 Histogram Based Tracker
  • 3.7.2 Optical Flow
  • 3.7.3 Point Tracker
  • 3.7.4 Kalman Filter
  • 3.7.5 Block Matcher
  • 3.8 Video Processing Using Simulink
  • Review Questions
  • 4 Pattern Recognition
  • 4.1 Introduction
  • 4.2 Toolboxes and Functions
  • 4.2.1 Computer Vision System Toolbox (CVST)
  • 4.2.2 Statistics and Machine Learning Toolbox (SMLT)
  • 4.2.3 Neural Network Toolbox (NNT)
  • 4.3 Data Acquisition
  • 4.4 Pre-processing
  • 4.5 Feature Extraction
  • 4.5.1 Minimum Eigenvalue Method
  • 4.5.2 Harris Corner Detector
  • 4.5.3 FAST Algorithm
  • 4.5.4 MSER Algorithm
  • 4.5.5 SURF Algorithm
  • 4.5.6 KAZE Algorithm
  • 4.5.7 BRISK Algorithm
  • 4.5.8 LBP Algorithm
  • 4.5.9 HOG Algorithm
  • 4.6 Clustering
  • 4.6.1 Similarity Metrics
  • 4.6.2 k-means Clustering
  • 4.6.3 Hierarchical Clustering
  • 4.6.4 GMM-Based Clustering
  • 4.7 Classification
  • 4.7.1 k-NN Classifiers
  • 4.7.2 Artificial Neural Network (ANN) classifiers
  • 4.7.3 Decision Tree Classifiers
  • 4.7.4 Discriminant Analysis Classifiers
  • 4.7.5 Naive Bayes Classifiers
  • 4.7.6 Support Vector Machine (SVM) Classifiers
  • 4.7.7 Classification Learner App
  • 4.8 Performance Evaluation
  • Review Questions
  • Function Summary
  • References
  • Index.

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