Uniqueness of the Gaussian Kernel for Scale-Space Filtering
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Adaptive histogram equalization and its variations
Computer Vision, Graphics, and Image Processing
Computer Vision
Digital Image Processing
Multiresolution Analysis of Ridges and Valleys in Grey-Scale Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Smoothed Local Symmetries and Their Implementation
Smoothed Local Symmetries and Their Implementation
Finding Edges and Lines in Images
Finding Edges and Lines in Images
The multiresolution intensity axis of symmetry and its application to image segmentation
The multiresolution intensity axis of symmetry and its application to image segmentation
Detecting Symmetry in Grey Level Images: The Global Optimization Approach
International Journal of Computer Vision
Shape-based features for cat ganglion retinal cells classification
Real-Time Imaging
Multiresolution Analysis of Ridges and Valleys in Grey-Scale Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Towards Segmentation from Multiple Cues: Symmetry and Color
Proceedings of the 10th International Workshop on Theoretical Foundations of Computer Vision: Multi-Image Analysis
A Cooperating Strategy for Objects Recognition
Shape, Contour and Grouping in Computer Vision
Multi-scale morphological modeling of a class of structural texture
Machine Graphics & Vision International Journal
Pyramid symmetry transforms: From local to global symmetry
Image and Vision Computing
Iterative symmetry detection: Shrinking vs. decimating patterns
Integrated Computer-Aided Engineering
Soft pyramid symmetry transforms
WILF'03 Proceedings of the 5th international conference on Fuzzy Logic and Applications
| Hi-index | 0.15 |
The authors present the intensity axis of symmetry (IAS) method for describing the shape of structures in grey-scale images. They describe the spatial and intensity variations of the image simultaneously rather than by the usual two-step process of using intensity properties of the image to segment an image into regions and describing the spatial shape of these regions. The result is an image shape description that is useful for a number of computer vision applications. The method relies on minimizing an active surface functional that provides coherence in both the spatial and intensity dimensions while deforming into an axis of symmetry. Shape-based image segmentation is possible by identifying image regions associated with individual components of the IAS. The resulting image regions have geometric coherence and correspond well to visually meaningful objects in medical images.