Ecole Supérieure des Sciences et Techniques de Tunis, University of Tunis, Tunis 1008, Tunisia.
IEEE Trans Image Process. 2011 Oct;20(10):2848-55. doi: 10.1109/TIP.2011.2134857.
This paper presents a novel approach to contour approximation carried out by means of the B-snake algorithm and the dynamic programming (DP) optimization technique. Using the proposed strategy for contour point search procedure, computing complexity is reduced to O(N×M(2)), whereas the standard DP method has an O(N×M(4)) complexity, with N being the number of contour sample points and M being the number of candidates in the search space. The storage requirement was also decreased from N×M(3) to N×M memory elements. Some experiments on noise corrupted synthetic image, magnetic resonance, and computer tomography medical images have shown that the proposed approach results are equivalent to those obtained by the standard DP algorithm.
本文提出了一种新的轮廓逼近方法，该方法通过 B 样条蛇算法和动态规划（DP）优化技术来实现。使用所提出的轮廓点搜索过程策略，计算复杂度降低到 O(N×M(2))，而标准的 DP 方法的复杂度为 O(N×M(4))，其中 N 是轮廓采样点的数量，M 是搜索空间中的候选数量。存储要求也从 N×M(3)降低到 N×M 个存储元件。对噪声污染的合成图像、磁共振和计算机断层扫描医学图像的一些实验表明，所提出的方法的结果与标准 DP 算法得到的结果相当。
