DocumentCode
922085
Title
Frame representations for texture segmentation
Author
Laine, Andrew ; Fan, Jian
Author_Institution
Dept. of Comput. & Inf. Sci., Florida Univ., Gainesville, FL, USA
Volume
5
Issue
5
fYear
1996
fDate
5/1/1996 12:00:00 AM
Firstpage
771
Lastpage
780
Abstract
We introduce a novel method of feature extraction for texture segmentation that relies on multichannel wavelet frames and 2-D envelope detection. We describe and compare two algorithms for envelope detection based on (1) the Hilbert transform and (2) zero crossings. We present criteria for filter selection and discuss quantitatively their effect on feature extraction. The performance of our method is demonstrated experimentally on samples of both natural and synthetic textures
Keywords
Hilbert transforms; feature extraction; filtering theory; image representation; image segmentation; image texture; wavelet transforms; 2D envelope detection; Hilbert transform; algorithms; feature extraction; filter selection; frame representations; multichannel wavelet frames; natural textures; performance; synthetic textures; texture segmentation; zero crossings; Calendars; Degradation; Filtering; Filters; Gaussian noise; Image restoration; Image segmentation; Pollution measurement; Signal restoration; Signal to noise ratio;
fLanguage
English
Journal_Title
Image Processing, IEEE Transactions on
Publisher
ieee
ISSN
1057-7149
Type
jour
DOI
10.1109/83.499915
Filename
499915
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