NDLI: Neural network-based segmentation of textures using Gabor features

Content Provider	IEEE Xplore Digital Library
Author	Ramakrishnan, A.G. Kumar Raja, S. Raghu Ram, H.V.
Copyright Year	2002
Description	Author affiliation: Dept. of Electr. Eng., Indian Inst. of Sci., Bangalore, India (Ramakrishnan, A.G.; Kumar Raja, S.; Raghu Ram, H.V.)
Abstract	The effectiveness of Gabor filters for texture segmentation is well known. In this paper, we propose a texture identification scheme, based on a neural network (NN) using Gabor features. The features are derived from both the Gabor cosine and sine filters. Through experiments, we demonstrate the effectiveness of a NN based classifier using Gabor features for identifying textures in a controlled environment. The neural network used for texture identification is based on the multilayer perceptron (MLP) architecture. The classification results obtained show an improvement over those obtained by K-means clustering and maximum likelihood approaches.
Sponsorship	IEEE Signal Process. Soc. IEEE Neural Network Council Swiss Nat. Sci. Found
Starting Page	365
Ending Page	374
File Size	551265
Page Count	10
File Format	PDF
ISBN	0780376161
DOI	10.1109/NNSP.2002.1030048
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-09-06
Publisher Place	Switzerland
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neural networks Gabor filters Frequency Multilayer perceptrons Multi-layer neural network Image segmentation Classification algorithms Clustering algorithms Robustness Satellites
Content Type	Text
Resource Type	Article

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