A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer Vision, Graphics, and Image Processing
Precision Edge Contrast and Orientation Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Algorithms for Low-Level Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Rotation invariance in gradient and higher order derivative detectors
Computer Vision, Graphics, and Image Processing
A taxonomy for texture description and identification
A taxonomy for texture description and identification
Computing oriented texture fields
CVGIP: Graphical Models and Image Processing
Multidimensional Orientation Estimation with Applications to Texture Analysis and Optical Flow
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Design and Use of Steerable Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computerized Flow Field Analysis: Oriented Texture Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
Identifying high level features of texture perception
CVGIP: Graphical Models and Image Processing
Multidimensional co-occurrence matrices for object recognition and matching
Graphical Models and Image Processing
On-Line Fingerprint Verification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using orientation tokens for object recognition
Pattern Recognition Letters
Deformable Kernels for Early Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiscale Characterization of Texture Anistropy
ICIP '97 Proceedings of the 1997 International Conference on Image Processing (ICIP '97) 3-Volume Set-Volume 3 - Volume 3
Scale-Adaptive Orientation Estimation
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
Multiscale estimation of vector field anisotropy application to texture characterization
Signal Processing - From signal processing theory to implementation
Steerable wedge filters for local orientation analysis
IEEE Transactions on Image Processing
Estimating local multiple orientations
Signal Processing
Machine Vision and Applications
Estimation of the orientation of textured patterns via wavelet analysis
Pattern Recognition Letters
Local orientation estimation in corrupted images
IWICPAS'06 Proceedings of the 2006 Advances in Machine Vision, Image Processing, and Pattern Analysis international conference on Intelligent Computing in Pattern Analysis/Synthesis
Hi-index | 0.01 |
This paper focuses on directional texture analysis. We propose a new approach for orientation estimation. This approach hinges on two classes of convolution masks, i.e. the gradient and the valleyness operators. We provide a framework for their optimization regarding bias reduction and noise robustness. As the gradient and the valleyness operators are complementary, we propose a combination named GV-JOE. This combination consists in using the gradient on inflexion pixels, the valleyness on crests and valleys, and a linear mixture of both elsewhere. We implement an adaptive selection of the size of our operators, in order to take into account the variations of the texture scale in the image. We apply our approach both on synthetic and natural textures. These experiments show that, when used separately, both classes of operators are more accurate than classical derivative approaches. In noisy cases, the GV-JOE implementation improves the robustness of our operators without affecting their accuracy. Moreover, compared to well-known orientation estimators, it gives the best estimates in the most difficult cases i.e. for high-frequency textures and low SNR.