The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.12 - December (2003 vol.25)
pp: 1639-1644
ABSTRACT
<p><b>Abstract</b>—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.</p>
INDEX TERMS
Texture segmentation, M-band wavelet packet frames, feature selection, fuzzy feature evaluation index, neural networks.
CITATION
Mausumi Acharyya, Rajat K. De, Malay K. Kundu, "Extraction of Features Using M-Band Wavelet Packet Frame and Their Neuro-Fuzzy Evaluation for Multitexture Segmentation", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.25, no. 12, pp. 1639-1644, December 2003, doi:10.1109/TPAMI.2003.1251158
17 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool