Region Based Contour Detection by Dynamic Programming

Dynamic programming (DP) is a popular technique for contour detection, particularly in biomedical image analysis. Although gradient information is typically used in such methods, it is not always a reliable measure to work with and there is a strong need of non-gradient based methods. In this paper we present a general framework for region based contour detection by dynamic programming. It is based on a global energy function which is approximated by a radial ray-wise summation to enable dynamic programming. Its simple algorithmic structure allows to use arbitrarily complex region models and model testing functions, in particular by means of techniques from robust statistics. The proposed framework was tested on synthetic data and real microscopic images. A performance comparison with the standard gradient-based DP and a recent non-gradient DP-based contour detection algorithm clearly demonstrates the superiority of our approach.