(2005) Multiscale object features from clustered complex wavelet coefficients. IEEE Workshop on Statistical Signal Processing Proceedings, 2005. pp. 437-441.Full text not available from this repository.
This paper introduces a method by which intuitive feature entities can be created from ILP (InterLevel Product) coefficients. The ILP transform is a pyramid of decimated complex-valued coefficients at multiple scales, derived from dual-tree complex wavelets, whose phases indicate the presence of different feature types (edges and ridges). We use an Expectation-Maximization algorithm to cluster large ILP coefficients that are spatially adjacent and similar in phase. We then demonstrate the relationship that these clusters possess with respect to observable image content, and conclude with a look at potential applications of these clusters, such as rotation- and scale-invariant object recognition. © 2005 IEEE.
|Divisions:||Div F > Signal Processing and Communications|
|Depositing User:||Cron Job|
|Date Deposited:||09 Dec 2016 17:19|
|Last Modified:||23 Feb 2017 00:36|