Abstract

We consider the problem of texture analysis with a fast algorithm. For that purpose we propose to use coefficients of the decomposition of co-occurrence matrices on an orthonormal and separable basis. We apply this method for texture discrimination, and we thus demonstrate with some examples its efficiency in terms of rapidity, discrimination performance, and robustness. We compare this method with classifiers that use a Fisher linear discrimination on features a priori defined in the co-occurrence matrices.

© 1997 Optical Society of America

Full Article  |  PDF Article
Related Articles
Comparative study of optical–digital vs all-digital techniques in textural pattern recognition

R. K. O'Toole and H. Stark
Appl. Opt. 19(15) 2496-2506 (1980)

Covariance-based approach to texture processing

Z. Q. Liu and S. V. R. Madiraju
Appl. Opt. 35(5) 848-853 (1996)

Automated defect detection system using wavelet packet frame and Gaussian mixture model

Soo Chang Kim and Tae Jin Kang
J. Opt. Soc. Am. A 23(11) 2690-2701 (2006)

References

You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Figures (5)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Tables (3)

You do not have subscription access to this journal. Article tables are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Equations (21)

You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Metrics

You do not have subscription access to this journal. Article level metrics are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription