Hands

1. Front Matter

   Pages i-vii

   PDF

2. Dealing with Highly Variable Patterns

   • U. Grenander, Y. Chow, D. M. Keenan

   Pages 1-7

3. Pattern Synthesis

   • U. Grenander, Y. Chow, D. M. Keenan

   Pages 8-38

4. Pattern Analysis

   • U. Grenander, Y. Chow, D. M. Keenan

   Pages 39-44

5. Pattern Synthesis: Experiments

   • U. Grenander, Y. Chow, D. M. Keenan

   Pages 45-54

6. Pattern Analysis — Experiments

   • U. Grenander, Y. Chow, D. M. Keenan

   Pages 55-63

7. Model Critique and Conclusions

   • U. Grenander, Y. Chow, D. M. Keenan

   Pages 65-66

8. Back Matter

   Pages 67-128

   PDF

In this book a global shape model is developed and applied to the analysis of real pictures acquired with a visible light camera under varying conditions of optical degradation. Computational feasibility of the algorithms derived from this model is achieved by analytical means. The aim is to develop methods for image understanding based on structured restoration, for example automatic detection of abnormalities. We also want to find the limits of applicability of the algorithms. This is done by making the optical degradations more and more severe until the algorithms no longer succeed in their task. This computer experiment in pattern theory is one of several. The others, LEAVES, X-RAYS, and RANGE are described elsewhere. This book is suitable for an advanced undergraduate or graduate seminar in pattern theory, or as an accompanying book for applied probability, computer vision, or pattern recognition.

• algorithms
• artificial intelligence
• cognition
• computer vision
• model
• pattern analysis
• pattern recognition

• Division of Applied Mathematics, Brown University, Providence, USA

  U. Grenander

• Institute of Mathematics, Academia Sinica, Taipei, Taiwan R.O.C.

  Y. Chow

• Department of Mathematics, University of Virginia, Charlottesville, USA

  D. M. Keenan

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