Extraction of features using M-band wavelet packet frame and their neuro-fuzzy evaluation for multitexture segmentation
- 8 December 2003
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in Ieee Transactions On Pattern Analysis and Machine Intelligence
- Vol. 25 (12), 1639-1644
- https://doi.org/10.1109/tpami.2003.1251158
Abstract
In this paper, we propose a scheme for segmentation of multitexture images. The methodology involves extraction of texture features using an overcomplete wavelet decomposition scheme called discrete M-band wavelet packet frame (DMbWPF). This is followed by the selection of important features using a neuro-fuzzy algorithm under unsupervised learning. A computationally efficient search procedure is developed for finding the optimal basis based on some maximum criterion of textural measures derived from the statistical parameters for each of the subbands. The superior discriminating capability of the extracted features for segmentation of various texture images over those obtained by several existing methods is established.Keywords
This publication has 17 references indexed in Scilit:
- Separability based tree structured local basis selection for texture classificationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Filtering for texture classification: a comparative studyIEEE Transactions on Pattern Analysis and Machine Intelligence, 1999
- Separability-based multiscale basis selection and feature extraction for signal and image classificationIEEE Transactions on Image Processing, 1998
- Frame representations for texture segmentationIEEE Transactions on Image Processing, 1996
- Design of efficient M-band coders with linear-phase and perfect-reconstruction propertiesIEEE Transactions on Signal Processing, 1995
- Texture analysis and classification with tree-structured wavelet transformIEEE Transactions on Image Processing, 1993
- Texture classification by wavelet packet signaturesIeee Transactions On Pattern Analysis and Machine Intelligence, 1993
- Wavelets and filter banks: theory and designIEEE Transactions on Signal Processing, 1992
- Analysis of multichannel narrow-band filters for image texture segmentationIEEE Transactions on Signal Processing, 1991
- A theory for multiresolution signal decomposition: the wavelet representationIeee Transactions On Pattern Analysis and Machine Intelligence, 1989