Detection of symmetric junctions in biological images using 2-D steerable wavelet transforms
We present a method for designing steerable wavelets that can detect local centers of symmetry in images. Based on this design, we then propose an algorithm for estimating the locations and the orientations of M-fold symmetric junctions in biological micrographs. The analysis with 2-D steerable wavelets allows us to have detections at different scales and arbitrary orientations. Owing to the steering property of our wavelets the detection is fast and accurate. We provide experimental results on both synthetic images and biological micrographs to demonstrate the performance of the algorithm.