Computer Vision in Control Systems. 6, Advances in practical applications

Computer Vision in Control Systems. 6, Advances in practical applications / Margarita N. Favorskaya, Lakhmi C. Jain, editors.

This book attempts to improve algorithms by novel theories and complex data analysis in different scopes including object detection, remote sensing, data transmission, data fusion, gesture recognition, and medical image processing and analysis. The book is directed to the Ph. D. students, professors...

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Bibliographic Details
Other Authors: Favorskaya, Margarita N., Jain, L. C.
Format: eBook
Language:English
Published: Cham : Springer, 2020.
Series:Intelligent systems reference library.
Subjects:
Computer vision.
Computer vision
Online Access:Click for online access
Table of Contents:
  • Intro
  • Preface
  • Contents
  • About the Editors
  • 1 Image Processing for Practical Applications
  • 1.1 Introduction
  • 1.2 Chapters in the Book
  • 1.3 Conclusions
  • References
  • 2 New Methods of Forming and Measurement of Sub-pixel Shift of Digital Images
  • 2.1 Introduction
  • 2.2 Shift Algorithm Based on Discrete Chebyshev Transformation
  • 2.3 Position Estimation in Noisy Images
  • 2.4 Analyze of Autocorrelation Function
  • 2.5 Shift's Estimation by Using Discriminator
  • 2.5.1 Discriminator Structure
  • 2.5.2 Distribution Law of Estimation
  • 2.5.3 Robust Estimate of Signal Parameter
  • 2.6 Conclusions
  • References
  • 3 The Characteristics of the Phase-Energy Image Spectrum
  • 3.1 Introduction
  • 3.2 The Model of One-Dimensional Energy-Phase Spectrum
  • 3.3 The Model of Two-Dimensional Phase-Energy Spectrum
  • 3.4 Conclusions
  • References
  • 4 Detectors Fields
  • 4.1 Introduction
  • 4.2 The Primitive Detectors Field
  • 4.3 Drift of the Detectors Field
  • 4.4 Two-Dimensional Discrete Filtering of Detectors Fields for Output Signals
  • 4.5 Experimental Studies
  • 4.6 Using Detectors Field Filtering in Images Affected by Motion Blur
  • 4.7 Conclusions
  • References
  • 5 Comparative Evaluation of Algorithms for Trajectory Filtering
  • 5.1 Introduction
  • 5.2 Target Motion Models
  • 5.3 Trajectory Filtration Algorithms
  • 5.4 Body-Fixed Frame
  • 5.5 Comparative Analysis of Filtration Efficiency
  • 5.6 Conclusions
  • References
  • 6 Watermarking Models of Video Sequences
  • 6.1 Introduction
  • 6.2 Related Work
  • 6.3 Watermarking Model of Videos in Uncompressed Domain
  • 6.4 Watermarking Models of Videos in Compressed Domain
  • 6.4.1 Watermarking Schemes for Compressed Video Sequences
  • 6.4.2 Watermarking Models for Three Strategies
  • 6.5 Basic Requirements for Watermarking Schemes
  • 6.6 Conclusions
  • References
  • 7 Experimental Data Acquisition and Management Software for Camera Trap Data Studies
  • 7.1 Introduction
  • 7.2 Related Work
  • 7.3 Camera Traps Data
  • 7.4 Proposed Software System
  • 7.4.1 Module of Data Management
  • 7.4.2 Module of Preliminary Analysis
  • 7.4.3 Module of Image Enhancement
  • 7.4.4 Module of Animal Detection
  • 7.4.5 Module of CNN Control
  • 7.4.6 Module of Semantic Description
  • 7.5 Conclusions
  • References
  • 8 Two-Stage Method for Polyps Segmentation in Endoscopic Images
  • 8.1 Introduction
  • 8.2 Related Work
  • 8.3 Proposed Two-Stage Approach for the Classification and Segmentation of Polyps
  • 8.3.1 The Idea of a Two-Stage Approach
  • 8.3.2 Databases
  • 8.3.3 Binary Classification Based on Global Features
  • 8.3.4 Segmentation Based on CNN
  • 8.4 Experimental Studies
  • 8.5 Conclusions
  • References
  • 9 Algorithms for Markers Detection on Facies Images of Human Biological Fluids in Medical Diagnostics
  • 9.1 Introduction
  • 9.2 The Examples of Images of Biological Liquids Facies
  • 9.3 The Image Preprocessing

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