摘要
基于特征提取的图像配准在医学领域得到广泛的应用。为了将尺度不变特性变换算法更好地运用到血管图像特征提取与匹配中去,根据血管图像特点,采用曲线拟合确定合适的低对比度阈值,并为了提高SIFT算法的处理速度以及匹配准确度,对SIFT算法的特征描述子进行降维处理,在特征点匹配阶段采用基于模比较的匹配方法,通过对比特征点描述向量模的关系寻找匹配点。实验结果及数据表明:改进后的算法在提高匹配速率和降低误匹配率方面均有提高,对临床血管疾病治疗有重要意义。
Image registration based on the feature extraction is widely used in the medical field.In order to apply the scale-invariant feature transform algorithm into feature extraction and matching of vascular images,a suitable low contrast threshold is determined with the curve fitting method according to the vascular image characteristic,besides,in order to improve the speed and matching accuracy of the SIFT algorithm,conduct dimensionality reduction on the feature descriptors of SIFT algorithm.A method based upon the modulus comparison was used for feature points matching,find the matching points by comparing the relationship between the feature points vector modulus.The experimental results and data show that the improved algorithm has increased the performance in improving the matching rate and lower false matching rate,and it is important for the clinical treatment of vascular disease.
出处
《电子测量技术》
2015年第12期63-66,共4页
Electronic Measurement Technology
关键词
尺度不变特征变换
特征点描述
特征点匹配
模比较
Scale-Invariant Feature Transform
feature points descriptor
feature matching
comparing modulus
