A comparative study on the K-views classifier and Markov random fields for image texture classification

2005 ◽  
Author(s):  
Minh Pham ◽  
Mei Xiang ◽  
Chih-Cheng Hung ◽  
Bor-Chen Kuo
Keyword(s):  
Comparative Study ◽  
Random Fields ◽  
Markov Random Fields ◽  
Texture Classification ◽  
Image Texture ◽  
Markov Random

Markov random fields for texture classification

1993 ◽  
Vol 14 (11) ◽  
pp. 907-914 ◽  
Author(s):  
Chaur-Chin Chen ◽  
Chung-Ling Huang
Keyword(s):  
Random Fields ◽  
Markov Random Fields ◽  
Texture Classification ◽  
Markov Random

scholarly journals A New Technique For Texture Classification Using Markov Random Fields

2006 ◽  
Vol 1 (2) ◽  
pp. 41
Author(s):  
Renato Salinas ◽  
Mauricio Gomez
Keyword(s):  
Random Fields ◽  
Markov Random Fields ◽  
Digital Images ◽  
Texture Classification ◽  
New Technique ◽  
Neural Net ◽  
Markov Random ◽  
Innovative Model ◽  
A New Technique

This paper proposes, applies and evaluates a new technique for texture classification in digital images. The work describes, as far as possible in a quantitative way, the concept of texture in digital images. Furthermore, we developed an innovative model that allows classifying and characterizing texture in digital images, to be used as a useful tool in noninvasive inspection of visual surfaces. The proposed methodology extracts the statistical order from an image of texture. The extraction of the high statistical order has been made using as a tool Markov Random Fields. The Backpropagation neural net is used for designing a classification module that will serve to test the performance of the configuration histograms, which are based on the statistical order. Furthermore, the research suggests the evaluation of the proposed technique from a qualitative perspective.

A Comparative Study of Energy Minimization Methods for Markov Random Fields

2006 ◽  
pp. 16-29 ◽  
Author(s):  
Richard Szeliski ◽  
Ramin Zabih ◽  
Daniel Scharstein ◽  
Olga Veksler ◽  
Vladimir Kolmogorov ◽  
...  
Keyword(s):  
Comparative Study ◽  
Random Fields ◽  
Energy Minimization ◽  
Markov Random Fields ◽  
Markov Random ◽  
Minimization Methods
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