**Author:** Gerhard Winkler

**Description:**

This second edition of G. Winkler's successful book on random field approaches to image analysis, related Markov Chain Monte Carlo methods, and statistical inference with emphasis on Bayesian image analysis concentrates more on general principles and models and less on details of concrete applications.

Addressed to students and scientists from mathematics, statistics, physics, engineering, and computer science, it will serve as an introduction to the mathematical aspects rather than a survey. Basically no prior knowledge of mathematics or statistics is required.

The second edition is in many parts completely rewritten and improved, and most figures are new. The topics of exact sampling and global optimization of likelihood functions have been added. This second edition comes with a CD-ROM by F. Friedrich,containing a host of (live) illustrations for each chapter. In an interactive environment, readers can perform their own experiments to consolidate the subject.

**Why?**

Good ol' question why. What does image recognition have to do with lottery predictions you ask? first what does it have that is **not** in common!

For starters, image recognition is not about prediction, its about inference or classification of historical data.

A qualified image in nature, such an image of a tree can be categorized by finding repetitive features (such as leaves, trunk, tree apples etc) in lottery no such a repetitive features exists, no image recognition can be applied to lottery data as no repetitive matrix can be found (some will disagree on this point!)

However if an image is hard to categorize, it does not have distinctive features, image recognition becomes very hard (i.e computing some polygons by a deterministic algorithm and arriving with solutions to an equation in some n-space represented by some complex polynomial) and that's where stochastic methods such as Monte Carlo comes along, by a massive random sampling bombardment a target image is dissected and compared to some large database containing samples of vast number of possible shapes i....

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