A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature detection from local energy
Pattern Recognition Letters
On the classification of image features
Pattern Recognition Letters
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Correlation Ratio as a New Similarity Measure for Multimodal Image Registration
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
Alignment by Maximization of Mutual Information
Alignment by Maximization of Mutual Information
3D-orientation space: filters and sampling
SCIA'03 Proceedings of the 13th Scandinavian conference on Image analysis
| Hi-index | 0.10 |
In this paper we propose a technique for the decomposition of a 3D image into a set of low level patterns associated to phase congruency, which we call visual patterns. Those patterns have frequency components in a wide range of bands that are aligned in phase. The method involves clustering of the band-pass filtered versions of the image according to a measure of congruence in phase or, what is equivalent, alignment in the filter's responses energy maxima. This is achieved by defining a distance between the responses of pairs of filters and applying a hierarchical clustering analysis to the resulting distance matrix. To measure the degree of maxima alignment we propose a set of alternative distances and study their suitability. From this study we conclude that a measure of linear dependence between the local energy of filters' responses is more appropriate than a more general measure of dependence.