摘要
提出了一种用于形状检索的基于多级三角形面积函数的傅里叶描述子.对形状轮廓上任一点,多级三角形面积函数通过轮廓的非等弧长分割计算得出,可以很好地描述形状的整体特征和局部细节特征.形状特征向量由多级三角形面积函数的低频傅里叶变换系数构成.在标准的MPEG-7形状图像库上对该方法进行了图像检索实验,并与已有的分别基于中心距离函数、面积函数、最远点距离函数、角度半径复函数、拱高半径复函数的傅里叶描述子以及混合傅里叶描述子进行了检索性能比较.实验结果表明,所提出的方法在相同查全率时具有最高的查准率,且具有较低的计算复杂度,证明该方法的有效性.
A novel Fourier descriptor based on multi-level triangular area functions （MTA） was proposed for shape retrieval. For each point on the shape contour, MTA values were derived from unequal-arc-length partitions of the shape contour. The MTA can finely capture the global features and local contour variations of the contour and their low- frequency Fourier coefficients were regarded as the feature vector for shape description. The image retrieval performance of the proposed method was evaluated on the standard MPEG-7 shape database and compared with those of Fourier descriptors derived from the centroid distance function, area function, farthest point distance function, angular radius function, arc-height radius complex function, and the combined Fourier descriptor. Experimental results demonstrate that the proposed method reaches the highest precision at the same recall value and has low complexity among these descriptors, showing its effectiveness.
出处
《北京科技大学学报》
EI
CAS
CSCD
北大核心
2013年第9期1201-1206,共6页
Journal of University of Science and Technology Beijing
基金
国家自然科学基金资助项目(61170116
61005009
60973064)
关键词
基于内容的检索
图像检索
几何学
形状描述
傅里叶变换
content based retrieval
image retrieval
geometry
shape description
Fourier transforms
