摘要
基于形状的目标检索技术难以检测噪声轮廓,无法兼顾表示其全局与局部显著性,导致检索精度不高。为此,提出一种图形检索算法。通过引入各向异性滤波,设计图形显著性检测算子,平滑噪声点与保留高曲率特征点,精确检测其形状显著性点,考虑形状轮廓点的总数与显著性位置,基于形状质心,定义相对角位置计算模型,并联合曲率函数,确定每个显著性点的表示值,将形状全局特征嵌入到局部细节中,联合动态规划算法,构建形状显著性相似度测量模型,进行特征点匹配,完成图形检索。测试结果表明,与基于形状的图像特征描述符相比,该算法具有更高的检索精度与更强的鲁棒性。
In order to solve the problem that it is difficult to detect the contour of the image based on the shape of the target,it can not take into account the global and local saliency,and the retrieval accuracy is not high. By introducing anisotropic filtering,design graphics saliency detection operator,to smooth the noise and retain high curvature features,its shape was accurate detection,considering the total shape of the contour points and the significant position,based on the shape of centroid,defined relative angular position calculation model,and combined with curvature function,determine the representation of each significant point values will shape the global features embedded into the local details,combined with dynamic programming algorithm to construct the shape significant similarity measurement model,feature point matching,complete graphics retrieval. The test results showthat the proposed algorithm has higher retrieval precision and stronger robustness than the shape based image descriptor.
出处
《计算机工程》
CAS
CSCD
北大核心
2017年第7期261-267,273,共8页
Computer Engineering
关键词
图形检索
各向异性滤波
形状质心
相对角位置
曲率函数
动态规划
image retrieval
anisotropic filtering
shape centroid
relative angular position
curvature function
dynamic programming
