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Hands-On Markov Models with Python

You're reading from   Hands-On Markov Models with Python Implement probabilistic models for learning complex data sequences using the Python ecosystem

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Product type Paperback
Published in Sep 2018
Publisher Packt
ISBN-13 9781788625449
Length 178 pages
Edition 1st Edition
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Authors (2):
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Ankur Ankan Ankur Ankan
Author Profile Icon Ankur Ankan
Ankur Ankan
Abinash Panda Abinash Panda
Author Profile Icon Abinash Panda
Abinash Panda
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Toc

2D HMM for Image Processing

In this chapter, we will introduce the application of HMM in the case of image segmentation. For image segmentation, we usually split up the given image into multiple blocks of equal size and then perform an estimation for each of these blocks. However, these algorithms usually ignore the contextual information from the neighboring blocks. To deal with that issue, 2D HMMs were introduced, which consider feature vectors to be dependent through an underlying 2D Markovian mesh. In this chapter, we will discuss how these 2D HMMs work and will derive parameter estimation algorithms for them. In this chapter, we will discuss the following topics:

  • Pseudo 2D HMMs
  • Introduction to 2D HMMs
  • Parameter learning in 2D HMMs
  • Applications
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