Abstract: According to the limited vision of spine image, this paper presents a method of automatic spine image moasic algorithm, which based on optimized MSFE（Multi-Scale Feature Extraction）. This algorithm devises two improved ways. One way is presented that the size of template can automatically adjust along with the scale factor changing, the other is that a bidirectional feature points matching algorithm is proposed. City-distance is used to judge similarity. Random sample consensus is used to guarantee stability and decide the transformation parameters of the image stiching, and a weighted average is used in the step of image fusion. The mosaic results of multiple spine images show that the algorithm has good real-time performance and robustness.

Key words: similar measurement, matching of feature points, Random Sample Consensus（RANSAC）, image mosaic, city-distance, spine image

摘要： 针对脊柱图像视野有限，提出一种基于优化MSFE的脊柱图像自动拼接算法。设计出一种基于尺度因子变化的高斯卷积模板尺寸自适应调整以及双向配对办法；相似性度量采用城市距离；利用RANSAC算法去除错配，从而确定待拼接图像之间的变换参数，最后利用加权平均对图像融合。对实际取得的多幅脊柱图像拼接结果表明该算法具有很好的实时性和鲁棒性。

关键词: 相似性度量, 特征点配对, 随机抽样一致性（RANSAC）, 图像拼接, 城市距离, 脊柱图像