Abstract
We propose a new method for shape recognition and retrieval based on dynamic programming. Our approach uses the dynamic programming algorithm to compute the optimal score and to find the optimal alignment between two strings. First, each contour of shape is represented by a set of points. After alignment and matching between two shapes, the contours are transformed into a string of symbols and numbers. Finally we find the best alignment of two complete strings and compute the optimal cost of similarity. In general, dynamic programming has two phases: the forward phase and the backward phase. In the forward phase, we compute the optimal cost for each subproblem. In the backward phase, we reconstruct the solution that gives the optimal cost. Our algorithm is tested in a database that contains various shapes such as MPEG-7.
Abstract (translated)
提出了一种基于动态规划的形状识别与检索新方法。我们的方法使用动态规划算法来计算最佳分数，并找出两个字符串之间的最佳对齐方式。首先，每个形状的轮廓由一组点表示。经过两个形状之间的对齐和匹配，轮廓被转换成一系列符号和数字。最后，我们找到两个完整字符串的最佳对齐方式，并计算出最佳相似成本。一般来说，动态规划有两个阶段：前阶段和后阶段。在正向阶段，我们计算每个子问题的最优成本。在后向阶段，我们重新构造出最优成本的解。我们的算法在包含各种形状（如MPEG-7）的数据库中进行了测试。
URL
https://arxiv.org/abs/1904.13219
