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Bio-Inspired Computing for Image and Video Processing

"Bio-Inspired Computing for Image and Video Processing" was published by Taylor & Francis Group in 2018 - Boca Raton, it has 404 pages and the language of the book is English.


“Bio-Inspired Computing for Image and Video Processing” Metadata:

  • Title: ➤  Bio-Inspired Computing for Image and Video Processing
  • Authors:
  • Language: English
  • Number of Pages: 404
  • Publisher: Taylor & Francis Group
  • Publish Date:
  • Publish Location: Boca Raton

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"Bio-Inspired Computing for Image and Video Processing" Description:

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Cover -- Half Title -- Title -- Copyrights -- Dedication -- Contents -- List of Figures -- List of Tables -- Preface -- Acknowledgments -- Editors -- Contributors -- Part I. Bio-Inspired Computing Models and Algorithms -- Chapter 1. Genetic Algorithm and BFOA-Based Iris and Palmprint Multimodal Biometric Digital Watermarking Models -- Chapter 2. Multilevel Thresholding for Image Segmentation Using Cricket Chirping Algorithm -- Chapter 3. Algorithms for Drawing Graphics Primitives on a Honeycomb Model-Inspired Grid -- Chapter 4. Electrical Impedance Tomography Using Evolutionary Computing: A Review -- Part II. Bio-Inspired Optimization Techniques -- Chapter 5. An Optimized False Positive Free Video Watermarking System in Dual Transform Domain -- Chapter 6. Bone Tissue Segmentation Using Spiral Optimization and Gaussian Thresholding -- Chapter 7. Digital Image Segmentation Using Computational Intelligence Approaches -- Chapter 8. Digital Color ImageWatermarking Using DWT SVD Cuckoo Search Optimization -- Chapter 9. Digital Image Watermarking Scheme in Transform Domain Using the Particle Swarm Optimization Technique -- Part III. Bio-Inspired Computing Applications to Image and Video Processing -- Chapter 10. Evolutionary Algorithms for the Efficient Design of Multiplier-Less Image Filter -- Chapter 11. Fusion of Texture and Shape-Based Statistical Features for MRI Image Retrieval System -- Chapter 12. Singular Value Decomposition-Principal Component Analysis-Based Object Recognition Approach -- Chapter 13. The KD-ORS Tree: An Efficient Indexing Technique for Content-Based Image Retrieval -- Chapter14. An Efficient Image Compression Algorithm Based on the Integration of a Histogram Indexed Dictionary and the Huffman Encoding for Medical Images -- Index

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