Texture segmentation by using adaptive polyphase subband decomposition

Date

2002-10-30

Author

Yaman, Mustafa
Atalay, Mehmet Volkan
Turker, M
Cetin, E
Gerek, ON

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In this study, a new texture segmentation method is proposed for texture analysis applications. The technique makes use of an adaptive polyphase subband decomposition to analyze textural blocks and extract the discriminating feature sets for segmentation of the images. The subband decomposition treats the texture blocks as 2-d signals having correlated spectral properties and the filter banks used split this signal into several frequency regions which are decorrelated by the decomposition. The filter coefficients are not static but modified through the process for adaptively analyzing the signal. The feature sets constructed according to the filter coefficients and the error image are fed to the classifier functions. Since the method decomposes the signal optimally, the feature extraction capability is boosted. The method is tested on artificial images produced by using Brodatz textures and texture blocks cut from IRS Pan satellite imagery.

URI

https://hdl.handle.net/11511/52957

Conference Name

17th International Symposium on Computer and Information Sciences

Collections

Department of Computer Engineering, Conference / Seminar

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Citation Formats

M. Yaman, M. V. Atalay, M. Turker, E. Cetin, and O. Gerek, “Texture segmentation by using adaptive polyphase subband decomposition,” presented at the 17th International Symposium on Computer and Information Sciences, Orlando, Florida, USA, 2002, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/52957.