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Advances in computational intelligence and robotics (ACIR) book series.
Examining fractal image processing and analysis / [edited by] Soumya Ranjan Nayak, Jibitesh Mishra. — 1 online resource. — (Advances in computational intelligence and robotics (ACIR) book series). — <URL:http://elib.fa.ru/ebsco/2244895.pdf>.

Record create date: 9/13/2019

Subject: Computer vision.; Image processing — Digital techniques.; Image analysis.; Computer vision.; Image analysis.; Image processing — Digital techniques.

Collections: EBSCO

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Digital image processing is a field that is constantly improving. Gaining high-level understanding from digital images is a key requirement for computing. One aspect of study that is assisting with this advancement is fractal theory. This new science has gained momentum and popularity as it has become a key topic of research in the area of image analysis. Examining Fractal Image Processing and Analysis is an essential reference source that discusses fractal theory applications and analysis, including box-counting analysis, multi-fractal analysis, 3D fractal analysis, and chaos theory, as well.

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Table of Contents

  • Title Page
  • Copyright Page
  • Book Series
  • Table of Contents
  • Detailed Table of Contents
  • Preface
  • Chapter 1: An Edge Detection Approach for Fractal Image Processing
  • Chapter 2: A Review on Chaos-Based Image Encryption Using Fractal Function
  • Chapter 3: Development of Algorithms for Medical Image Compression
  • Chapter 4: Empirical Performance Analysis of Wavelet Transform Coding-Based Image Compression Techniques
  • Chapter 5: A Performance Study of Image Quality Attributes on Smoothened Image Obtained by Anisotropic Diffusion-Based Models
  • Chapter 6: A Review of Contemporary Image Compression Techniques and Standards
  • Chapter 7: Bio-Medical Image Processing
  • Chapter 8: Fatigue Monitoring for Drivers in Advanced Driver-Assistance System
  • Chapter 9: Automatic Article Detection in a Jumbled Scene Using Point Feature Matching
  • Chapter 10: R-HOG Feature-Based Off-Line Odia Handwritten Character Recognition
  • Chapter 11: Image Enhancement
  • Chapter 12: Analysis of Biomedical Image for Alzheimer's Disease Detection
  • Chapter 13: An Algorithmic Approach Based on CMS Edge Detection Technique for the Processing of Digital Images
  • Compilation of References
  • About the Contributors
  • Index

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