摘要：

为充分利用多核计算资源提高图像匹配识别的实时性,设计一种基于改进最小距离法的图像匹配并行化算法。选取标准化欧氏距离来代替简单欧氏距离作为特征的相似性度量,同时在多核计算机上采用MPI+OpenMP混合编程模型对该算法进行仿真验证。结果表明,与基于最小 距离法的图像匹配算法相比,该算法可以减少匹配误差和匹配运算时间,并且MPI+OpenMP混合编程模型具有较好的加速比和并行计算效率。

关键词: 图像匹配, 决策理论, 最小距离法, 混合编程模型, 多核计算机

Abstract:

In order to take advantage of multi-core computing resources to improve the real-time performance of image matching identification,image matching parallel algorithm based on improved minimum distance method is designed.The standard euclidean distance is chosen to replace the simple euclidean distance as the similarity measure of the features,and the MPI+OpenMP hybrid programming model is used to verify the algorithm on multi-core computers.The results show that,the algorithm can reduce the matching error and matching operation time,moreover,MPI+OpenMP hybrid programming model has good speed-up ratio and parallel computational efficiency.

Key words: image matching, decision theory, minimum distance method, hybrid programming model, multi-core computer

中图分类号: 

• TP391.41