Author(s): LU Yu-wei, HU Jun
Pages: 40-44
Year: 2016 Issue:  4
Journal: Information of Medical Equipment
Keyword:  scale-invariant feature transform; speeded up robust features; image matching; K-nearest neighbor algorithm;
Abstract: The paper adopted the matching algorithm based on characteristic points to accomplish image matching in experimental medicine. The two algorithms: scale-invariant feature transform (SIFT) and speeded up robust features (SURF) were compared in aspects of characteristic points, characteristic extraction time and matching veracity. Then the K-nearest neighbor (KNN) algorithm was used to eliminate mismatching points. The paper also carried on statistical analysis of the results of random sample consensus (RANSAC) and least median of squres (LMEDS) as well as the correlation between matching veracity and algorithms. This research established a medical image matching platform based on characteristic points in order to provide a research basis for the further research and improvement of medical image matching.