1.

Record Nr.

UNINA9910455860003321

Titolo

Progress in computer vision and image analysis [[electronic resource] /] / editors, Horst Bunke ... [et al.]

Pubbl/distr/stampa

Singapore, : World Scientific, c2010

ISBN

1-282-76047-5

9786612760471

981-283-446-X

Descrizione fisica

1 online resource (591 p.)

Collana

Series in machine perception and artificial intelligence ; ; 73

Altri autori (Persone)

BunkeHorst

Disciplina

006.37

Soggetti

Computer vision

Image analysis

Electronic books.

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references and indexes.

Nota di contenuto

CONTENTS; Preface; 1. An appearance-based method for parametric video registration X. Orriols, L. Barceló 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 Andrade1. Introduction; 2. The interactive image smoothing and segmentation algorithm - ISS; 2.1. Edge preserving smoothing under controlled curvature motion; 2.1.1. Stopping criteria for curvature based denoising; 2.1.2. Effect of denoising on the ISS; 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. Turiel3.1.



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 MRI4.3. 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. Günter 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 schemes5.4.1. 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-Shafer's basic probability assignment based on fuzzy membership functions A. O. Boudraa et al.

Sommario/riassunto

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 students.  <i>Sample Chapter(s)</i><br>Chapter 1: An Appearance-Based Method for Parametric Video Registration (2,352 KB)<br> <br><i>Contents: </i><ul><li>An Appearance-Based Method for Parametric Video Registration <i>(X Orriols et al.)</i></li><li>Relevance of Multifractal Textures in Static Imag