||Cleju, I., Fränti, P., Wu, X.
||Clustering by principal curve with tree structure
||Data clustering is intensively used in signal processing in
tasks such as multimedia compression, segmentation and pattern matching.
In this work we extend the use of principal curves in clustering to
complex multidimensional datasets. The use of principal curve in
clustering is limited for high complexity data. Automatic
parameterization of the principal curve to assure good results for
different datasets is a difficult task. We propose to use the tree
structure to capture the general settlement of the data. Using this
topology, regions of the dataset can be extracted, individually
clustered using the principal curve and then optimally recombined. The
experiments show the improvement of the new method over the principal
curve based clustering and the good performance compared to other