A new active shape models (ASMs) was presented, which is driven by scale invariant feature transform (SIFT) local descriptor instead of normalizing first order derivative profiles in the original formulation, to segme...A new active shape models (ASMs) was presented, which is driven by scale invariant feature transform (SIFT) local descriptor instead of normalizing first order derivative profiles in the original formulation, to segment lung fields from chest radiographs. The modified SIFT local descriptor, more distinctive than the general intensity and gradient features, is used to characterize the image features in the vicinity of each pixel at each resolution level during the segmentation optimization procedure. Experimental results show that the proposed method is more robust and accurate than the original ASMs in terms of an average overlap percentage and average contour distance in segmenting the lung fields from an available public database.展开更多
文摘针对油田遥感图像在灰度有明显差异的情况下,联合位置、尺度和方向的尺度不变特征变换(PSO-SIFT)算法很难为其找到足够多的正确对应关系,且花费时间较长的问题,提出一种基于改进PSO-SIFT算法的图像匹配算法.首先采用“回”字型分块思想构建特征描述符,降低特征描述子的维度;然后使用基于全局运动建模的双边函数(BF)算法与快速样本共识(FSC)算法相结合的匹配策略,对所得的匹配对进行误匹配剔除,以增加正确匹配的数量;最后将该算法与4种同类算法及原PSO-SIFT算法进行对比.实验结果表明,该算法比同类算法精度更高,与原算法相比不仅保证了图像匹配的精度,正确匹配对数量也增加了约3倍,且匹配时间约缩短20 s.
基金The National Natural Science Foundation of China(No60271033)
文摘A new active shape models (ASMs) was presented, which is driven by scale invariant feature transform (SIFT) local descriptor instead of normalizing first order derivative profiles in the original formulation, to segment lung fields from chest radiographs. The modified SIFT local descriptor, more distinctive than the general intensity and gradient features, is used to characterize the image features in the vicinity of each pixel at each resolution level during the segmentation optimization procedure. Experimental results show that the proposed method is more robust and accurate than the original ASMs in terms of an average overlap percentage and average contour distance in segmenting the lung fields from an available public database.