Wavelet-Based Identification and Classification of Local Symmetries in Microscopy Images
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.
2014
Beijing, People's Republic of China
1035
1038
REVIEWED