DocumentCode
2693171
Title
Comparative study of noise-tolerant texture classification
Author
Ejell, B.
Author_Institution
Dept. of Comput. Sci., Central Connecticut State Univ., New Britain, CT
Volume
3
fYear
1994
fDate
2-5 Oct 1994
Firstpage
2431
Abstract
The effectiveness of four types of texture features are compared in performing noise-tolerant texture classification. The four types of texture features investigated are: edge separation texture features; standard cooccurrence matrix features; cooccurrence matrix features of directionally-smoothed texture samples; and the Fourier power and phase spectrum features of Liu and Jernigan (1990). All methods, except standard cooccurrence matrix features, performed well
Keywords
Fourier transform spectra; feature extraction; image classification; image texture; Fourier power; cooccurrence matrix features; directionally-smoothed texture samples; edge separation features; noise-tolerant texture classification; phase spectrum features; texture features; Computed tomography; Computer science; Fluctuations; Humans; Image edge detection; Image texture; Layout; Noise level; Psychology; White noise;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man, and Cybernetics, 1994. Humans, Information and Technology., 1994 IEEE International Conference on
Conference_Location
San Antonio, TX
Print_ISBN
0-7803-2129-4
Type
conf
DOI
10.1109/ICSMC.1994.400231
Filename
400231
Link To Document