compendium

paper information and status

D. C. Balcan, G. Srinivasa, M. C. Fickus and J. Kovačević. Guaranteeing convergence of iterative skewed voting algorithms for image segmentation. Appl. Comput. Harmon. Anal., 33(2):300-308, Sept. 2012.


[ pdf | @ ScienceDirect | bibtex]


abstract

In this paper we provide rigorous proof for the convergence of an iterative voting-based image segmentation algorithm called Active Masks. Active Masks (AM) was proposed to solve the challenging task of delineating punctate patterns of cells from fluorescence microscope images. Each iteration of AM consists of a linear convolution composed with a nonlinear thresholding; what makes this process special in our case is the presence of additive terms whose role is to "skew" the voting when prior information is available. In real-world implementation, the AM algorithm always converges to a fixed point. We study the behavior of AM rigorously and present a proof of this convergence. The key idea is to formulate AM as a generalized (parallel) majority cellular automaton, adapting proof techniques from discrete dynamical systems.


code

The zipped archive contains the Matlab code to generate the results in the paper.

[download]


This work is licensed under a Creative Commons GNU General Public License. To view a copy of this license, visit http://creativecommons.org/licenses/GPL/2.0. If you use this code or any part thereof in your research or publication, please also include a reference to this paper. Thank you!


proofs

All necessary proofs are included in the paper.


contact

For more information or to report bugs contact jelenak at cmu dot edu.