Rotation and scale invariant wavelet feature for content-based texture image retrieval
Journal of the American Society for Information Science and Technology
Proceedings of the Joint IAPR International Workshops on Advances in Pattern Recognition
Log-Polar Wavelet Energy Signatures for Rotation and Scale Invariant Texture Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Rotation-invariant texture feature for image retrieval
Computer Vision and Image Understanding
WAMUS'05 Proceedings of the 5th WSEAS International Conference on Wavelet Analysis and Multirate Systems
Rotation and Scale Invariant Texture Analysis with Tunable Gabor Filter Banks
PSIVT '09 Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology
Image Segmentation based on Inter-feature Distance Maps
Proceedings of the 2005 conference on Artificial Intelligence Research and Development
Rotation- and scale-invariant texture classification using log-polar and ridgelet transforms
Machine Graphics & Vision International Journal
Invariant texture classification for biomedical cell specimens via non-linear polar map filtering
Computer Vision and Image Understanding
Content based annotation and retrieval in RAIDER
IRSG'98 Proceedings of the 20th Annual BCS-IRSG conference on Information Retrieval Research
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K Abstract: An efficient and accurate method of extracting rotation invariant texture features via a multichannel Gabor filtering technique is presented. A main focus of the paper is a thorough investigation into the optimum parameter settings for the method. Experiments include the exploration of different frequency combinations, sampling intervals and number of features. The optimum settings are used to test the method's texture classification abilities on a database of over 1320 images originating from 44 different texture classes. The resistance to noise is measured via the addition of various levels of Gaussian noise to each image before classification.