• Radon transform orientation es...

*Result*: Radon transform orientation estimation for rotation invariant texture analysis.

Title:
Radon transform orientation estimation for rotation invariant texture analysis.
Authors:
Jafari-Khouzani K; Radiology Image Analysis Lab, Henry Ford Health System, One Ford Place, 2F (Box 82), Detroit, MI 48202, USA. kjafari@rad.hfh.edu, Soltanian-Zadeh H Sr
Source:
IEEE transactions on pattern analysis and machine intelligence [IEEE Trans Pattern Anal Mach Intell] 2005 Jun; Vol. 27 (6), pp. 1004-8.
Publication Type:
Evaluation Study; Journal Article; Research Support, N.I.H., Extramural; Research Support, U.S. Gov't, P.H.S.
Language:
English
Journal Info:
Publisher: IEEE Computer Society Country of Publication: United States NLM ID: 9885960 Publication Model: Print Cited Medium: Print ISSN: 0162-8828 (Print) Linking ISSN: 00985589 NLM ISO Abbreviation: IEEE Trans Pattern Anal Mach Intell Subsets: MEDLINE
Imprint Name(s):
Original Publication: [New York] IEEE Computer Society.
MeSH Terms:
Algorithms* , Artificial Intelligence*, Image Interpretation, Computer-Assisted/*methods , Information Storage and Retrieval/*methods , Pattern Recognition, Automated/*methods, Image Enhancement/methods ; Cluster Analysis ; Computer Graphics ; Numerical Analysis, Computer-Assisted ; Reproducibility of Results ; Sensitivity and Specificity ; Signal Processing, Computer-Assisted
References:
IEEE Trans Image Process. 1996;5(10):1423-34. (PMID: 18290060)
IEEE Trans Image Process. 1999;8(2):255-69. (PMID: 18267472)
IEEE Trans Image Process. 2004 Jun;13(6):782-91. (PMID: 15648869)
IEEE Trans Image Process. 2005 Jun;14(6):783-95. (PMID: 15971777)
IEEE Trans Image Process. 2002;11(8):825-37. (PMID: 18244677)
IEEE Trans Pattern Anal Mach Intell. 2005 Jun;27(6):1004-8. (PMID: 15945146)
Grant Information:
R01 EB002450 United States EB NIBIB NIH HHS
Entry Date(s):
Date Created: 20050611 Date Completed: 20050705 Latest Revision: 20250529
Update Code:
20260130
PubMed Central ID:
PMC2706151
DOI:
10.1109/TPAMI.2005.126
PMID:
15945146
Database:
MEDLINE

*Further Information*

*This paper presents a new approach to rotation invariant texture classification. The proposed approach benefits from the fact that most of the texture patterns either have directionality (anisotropic textures) or are not with a specific direction (isotropic textures). The wavelet energy features of the directional textures change significantly when the image is rotated. However, for the isotropic images, the wavelet features are not sensitive to rotation. Therefore, for the directional textures, it is essential to calculate the wavelet features along a specific direction. In the proposed approach, the Radon transform is first employed to detect the principal direction of the texture. Then, the texture is rotated to place its principal direction at 0 degrees. A wavelet transform is applied to the rotated image to extract texture features. This approach provides a features space with small intraclass variability and, therefore, good separation between different classes. The performance of the method is evaluated using three texture sets. Experimental results show the superiority of the proposed approach compared with some existing methods.*