Neural network-based segmentation of textures using Gabor features
Tóm tắt
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.
Từ khóa
#Neural networks #Gabor filters #Frequency #Multilayer perceptrons #Multi-layer neural network #Image segmentation #Classification algorithms #Clustering algorithms #Robustness #SatellitesTài liệu tham khảo
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