Progress In Computer Vision And Image Analysis.

This book is a collection of scientific papers published during the last five years, showing a broad spectrum of actual research topics and techniques used to solve challenging problems in the areas of computer vision and image analysis. The book will appeal to researchers, technicians and graduate...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Formato: Electrónico eBook
Idioma:Inglés
Publicado: World Scientific 2009.
Temas:
Computer vision.
Image analysis.
Vision par ordinateur.
Analyse d'images.
Computer vision
Image analysis
Electronic resource.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Cover13;
  • CONTENTS
  • Preface
  • 1. An appearance-based method for parametric video registration X. Orriols, L. Barcel180;o and X. Binefa
  • 1.1. Introduction
  • 1.2. Appearance Based Framework for Multi-Frame Registration
  • 1.2.1. Appearance Representation Model
  • 1.2.2. Polynomial Surface Model
  • 1.2.3. The Algorithm
  • 1.3. Experimental Results
  • 1.3.1. Selecting a Reference Frame. Consequences in the Registration
  • 1.3.2. Analyzing the Complexity in the Polynomial Model. Towards 3D Affine Reconstruction
  • 1.4. Summary and Conclusions
  • Acknowledgments
  • References
  • 2. An interactive algorithm for image smoothing and segmentation M.C. de Andrade
  • 1. Introduction
  • 2. The interactive image smoothing and segmentation algorithm
  • ISS
  • 2.1. Edge preserving smoothing under controlled curvature motion
  • 2.2. The interactive region growing and merging step
  • 2.3. The ISS algorithm steps
  • 3. Applications
  • 4. Conclusions and Outlook
  • Acknowledgments
  • Appendix A. ISS Pseudo-code
  • Appendix B. ISS Execution time for known test-images
  • References
  • 3. Relevance of multifractal textures in static images A. Turiel
  • 3.1. Introduction
  • 3.2. Multifractal framework
  • 3.3. Multifractal decomposition
  • 3.4. Reconstructing from edges
  • 3.5. Relevance of the fractal manifolds
  • 3.6. Conclusions
  • Acknowledgements
  • References
  • 4. Potential fields as an external force and algorithmic improvements in deformable models A. Caro et al.
  • 4.1. Introduction
  • 4.1.1. Overview on Active Contours
  • 4.1.2. Scope and purpose of the research
  • 4.2. Algorithm Design
  • 4.2.1. Standard Deformable Models
  • 4.2.2. The new approach for Deformable Models
  • 4.2.3. A practical application: DeformableModels on Iberian ham MRI
  • 4.3. Practical Results and their Discussion
  • 4.4. Conclusions
  • Acknowledgements
  • References
  • 5. Optimization of weights in a multiple classifier handwritten word recognition system using a genetic algorithm S. G168;unter and H. Bunke
  • 5.1. Introduction
  • 5.2. Handwritten word recognizer
  • 5.2.1. Preprocessing
  • 5.2.2. Feature extraction
  • 5.2.3. Hidden Markov models
  • 5.3. Ensemble creation methods
  • 5.3.1. Issues in ensemble creation
  • 5.3.2. Bagging
  • 5.3.3. AdaBoost
  • 5.3.4. Random subspace method
  • 5.3.5. Architecture variation
  • 5.4. Combination schemes
  • 5.4.1. Maximum score rule
  • 5.4.2. Performance weighted voting
  • 5.4.3. Weighted voting using weights calculated by a genetic algorithm
  • 5.4.4. Voting with ties handling
  • 5.5. Genetic algorithm for the calculation of the weights used by weighted voting
  • 5.5.1. Chromosome representation and fitness
  • 5.5.2. Initialization and termination
  • 5.5.3. Crossover operator
  • 5.5.4. Mutation operator
  • 5.5.5. Generation of a new population
  • 5.6. Experiments
  • 5.7. Conclusions
  • Acknowledgments
  • Appendix A. HandwrittenWord Samples
  • References
  • 6. Dempster-Shafers basic probability assignment based on fuzzy membership functions A.O. Boudraa et al.
  • 6.1. Introduction
  • 6.2. Dempster-Shafer theory
  • 6.3. Fuzzy approach
  • 6.4. Basic probability assignment
  • 6.5. Results
  • 6.6. Conclusion
  • References
  • 7. Automatic instrument localization in laparoscopic surgery J. Climent and P. Mars
  • 7.1. Introduction.

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