A model-based method for rotation invariant texture classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Local linear transforms for texture measurements
Signal Processing
Texture discrimination by Gabor functions
Biological Cybernetics
Modeling and Segmentation of Noisy and Textured Images Using Gibbs Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Gabor phase in texture discrimination
Signal Processing
Unsupervised texture segmentation using Gabor filters
Pattern Recognition
Texture classification using non-separable two-dimensional wavelets
Pattern Recognition Letters
Texture classification using multiresolution Markov random field models
Pattern Recognition Letters
Texture Classification by Wavelet Packet Signatures
IEEE Transactions on Pattern Analysis and Machine Intelligence
Texture classification using wavelet transform
Pattern Recognition Letters
Rotation invariant texture classification using even symmetric Gabor filters
Pattern Recognition Letters
Rotation-invariant texture classification using modified Gabor filters
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol. 1)-Volume 1 - Volume 1
Rotation and scale invariant texture features using discrete wavelet packet transform
Pattern Recognition Letters
A new robust circular Gabor based object matching by using weighted Hausdorff distance
Pattern Recognition Letters
Segmentation of Gabor-filtered textures using deterministic relaxation
IEEE Transactions on Image Processing
Rotation-invariant texture classification using a complete space-frequency model
IEEE Transactions on Image Processing
Statistical texture characterization from discrete wavelet representations
IEEE Transactions on Image Processing
Wavelet-based rotational invariant roughness features for texture classification and segmentation
IEEE Transactions on Image Processing
Unsupervised texture segmentation of images using tuned matched Gabor filters
IEEE Transactions on Image Processing
Optimal Gabor filters for texture segmentation
IEEE Transactions on Image Processing
Texture classification and segmentation using wavelet frames
IEEE Transactions on Image Processing
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Texture based image analysis techniques have been widely employed in the interpretation of earth cover images obtained using remote sensing techniques, seismic trace images, medical images and in query by content in large image data bases. The development in multiresolution analysis such as wavelet transform leads to the development of adequate tools to characterize different scales of textures effectively. But, the wavelet transform lacks in its ability to decompose input image into multiple orientations and this limits their application to rotation invariant image analysis. This paper presents a new approach for rotation invariant texture classification using Gabor wavelets. Gabor wavelets are the mathematical model of visual cortical cells of mammalian brain and using this, an image can be decomposed into multiple scales and multiple orientations. The Gabor function has been recognized as a very useful tool in texture analysis, due to its optimal localization properties in both spatial and frequency domain and found widespread use in computer vision. Texture features are found by calculating the mean and variance of the Gabor filtered image. Rotation normalization is achieved by the circular shift of the feature elements, so that all images have the same dominant direction. The texture similarity measurement of the query image and the target image in the database is computed by minimum distance criterion.