Filtering for Texture Classification: A Comparative Study
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Two-Point Correlation Function: A Measure of Interclass Separability
Journal of Mathematical Imaging and Vision
Texture classification using wavelet transform
Pattern Recognition Letters
Defect detection in textured surfaces using color ring-projection correlation
Machine Vision and Applications
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
Quantification of trabecular bone mass and orientation using Gabor wavelets
Proceedings of the 2003 ACM symposium on Applied computing
Digital image processing techniques for automatic textile quality control
Systems Analysis Modelling Simulation - Special issue: Digital signal processing and control
Texture segmentation using wavelet transform
Pattern Recognition Letters
Learning to detect texture objects by artificial immune approaches
Future Generation Computer Systems - Special issue: Geocomputation
Reduced Complexity Rotation Invariant Texture Classification Using a Blind Deconvolution Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Texture classification using Gabor wavelets based rotation invariant features
Pattern Recognition Letters
Expert Systems with Applications: An International Journal
Texture classification using Gabor wavelets based rotation invariant features
Pattern Recognition Letters
An automated inspection system for textile fabrics based on Gabor filters
Robotics and Computer-Integrated Manufacturing
Texture description using different wavelet transforms based on statistical parameters
WAV'08 Proceedings of the 2nd WSEAS International Conference on Wavelets Theory and Applications in Applied Mathematics, Signal Processing and Modern Science
Recycled paper visual indexing for quality control
Expert Systems with Applications: An International Journal
Viewpoint Invariant Texture Description Using Fractal Analysis
International Journal of Computer Vision
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
Centroid neural network with chi square distance measure for texture classification
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Residues of morphological filtering by reconstruction for texture classification
Pattern Recognition
Texture based prelens tear film segmentation in interferometry images
Machine Vision and Applications
Machine Vision and Applications
A brushlet-based feature set applied to texture classification
CIS'04 Proceedings of the First international conference on Computational and Information Science
Gabor kernels for textured image representation and classification
CIARP'06 Proceedings of the 11th Iberoamerican conference on Progress in Pattern Recognition, Image Analysis and Applications
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
Rotation-Invariant texture classification using steerable gabor filter bank
ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
| Hi-index | 0.02 |
Recent studies have confirmed that the multichannel Gabor decomposition represents an excellent tool for image segmentation and boundary detection. Unfortunately, this approach when used for unsupervised image analysis tasks imposes excessive storage requirements due to the nonorthogonality of the basis functions and is computationally highly demanding. In this correspondence, we propose a novel method for efficient image analysis that uses tuned matched Gabor filters. The algorithmic determination of the parameters of the Gabor filters is based on the analysis of spectral feature contrasts obtained from iterative computation of pyramidal Gabor transforms with progressive dyadic decrease of elementary cell sizes. The method requires no a priori knowledge of the analyzed image so that the analysis is unsupervised. Computer simulations applied to different classes of textures illustrate the matching property of the tuned Gabor filters derived using our determination algorithm. Also, their capability to extract significant image information and thus enable an easy and efficient low-level image analysis will be demonstrated