|Title||Moment Invariants for the Analysis of 2D Flow Fields
|in||IEEE Transactions on Visualization and Computer Graphics (Proceedings IEEE Visualization 2007)|
Michael Schlemmer, Manuel Heringer, Florian Morr, Ingrid Hotz, Martin Hering-Bertram, Christoph Garth, Wolfgang Kollmann, Bernd Hamann, Hans Hagen |
|Keyword(s)||Flow Visualization, Feature Detection, Pattern Extraction, Image Processing|
We present a novel approach for analyzing two-dimensional (2D) ﬂow ﬁeld data based on the idea of invariant moments. Moment invariants have traditionally been used in computer vision applications, and we have adapted them for the pur pose of interactive exploration of ﬂow ﬁeld data. The new class of moment invariants we have developed allows us to extract and visualize 2D ﬂow patterns, invariant under translation, scaling, and rotation. With our approach one can study arbitrar y ﬂow patterns by searching a given 2D ﬂow data set for any type of pattern as speciﬁed by a user. Further, our approach suppor ts the computation of moments at multiple scales, facilitating fast pattern extraction and recognition. This can be done for critical point classiﬁcation, but also for patterns with greater complexity. This multi-scale moment representation is also valuable for the comparative visualization of ﬂow ﬁeld data. The speciﬁc novel contributions of the work presented are the mathematical derivation of the new class of moment invariants, their analysis regarding critical point features, the efﬁcient computation of a novel feature space representation, and based upon this the development of a fast pattern recognition algorithm for complex ﬂow structures.