A Comparison of Matrix Texture Features Using a Maximum Likelihood Texture Classifier

Jon R. Berry Jr.; John Goutsias

doi:10.1117/12.970043

1 November 1989 A Comparison of Matrix Texture Features Using a Maximum Likelihood Texture Classifier

Jon R. Berry Jr., John Goutsias

Proceedings Volume 1199, Visual Communications and Image Processing IV; (1989) https://doi.org/10.1117/12.970043
Event: 1989 Symposium on Visual Communications, Image Processing, and Intelligent Robotics Systems, 1989, Philadelphia, PA, United States

Abstract

The performance of various matrix features in classifying synthetic and natural textures is compared by using the features directly in a maximum likelihood texture classifier (MLTC). The matrix texture features under consideration include the spatial gray level dependence matrix (SGLDM), the neighboring gray level dependence matrix (NGLDM) and the neighboring spatial gray level dependence matrix (NSGLDM). By adopting the MLTC we avoid the various problems associated with the use of scalar features extracted from the matrices under consideration, while we obtain excellent classification results.

Citation Download Citation

Jon R. Berry Jr. and John Goutsias "A Comparison of Matrix Texture Features Using a Maximum Likelihood Texture Classifier", Proc. SPIE 1199, Visual Communications and Image Processing IV, (1 November 1989); https://doi.org/10.1117/12.970043

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available