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Wavelet-Based Identification and Classification of Local Symmetries in Microscopy Images

Z. Püspöki, M. Unser

Proceedings of the Eleventh IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI'14), Beijing, People's Republic of China, April 29-May 2, 2014, pp. 1035-1038.



We present a method for the identification and classification of local symmetries in biological images. We aim at obtaining a precise estimate of symmetric junctions in a scale and rotation invariant way. The proposed method is template-free, which allows the test of any combination of arbitrary symmetry orders in an effective way.

Our measure of local symmetry is derived from a circular harmonic wavelet analysis. The basis functions exhibit different symmetry orders. We use this measure to formulate a classifier to label the different junctions into one of several symmetry classes.

We present experimental results, and validate our method using both on synthetic images and biological micrographs.


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