Scale Curvature and Fourier Shape Descriptor For Binary Image Retrieval
Contour shape descriptors are among the important shape description methods.Nevertheless,most of the reported descriptors still face accuracy and computational challenges.Fourier descriptor (FD) and curvature scale space descriptors (CSSD) are widely used as contour shape descriptors for image retrieval in the literature.Fourier descriptors are considered to be promising descriptors as they are based on sound theoretical foundation,and possess computational efficiency and attractive invariance properties.In this paper,we propose a novel Fourier descriptor based on contour curvature and apply it in binary image retrieval.The invariant descriptor is derived from the 2-D Fourier transform of the Curvature-Scale Image.This allows the descriptor to capture detailed dynamics of the shape curvature and enhance the efficiency of the shape matching process.Experiments using images from the MPEG-7 database have been conducted to compare the performance of the proposed descriptor with the Curvature-Scale-Space Descriptor (CSSD),and the Generic Fourier Descriptor (GFD).The proposed descriptor demonstrated superior performance.
multiscale curvature fourier descriptor binary image retrieval invariant
Hong SHAO Dian WANG Wencheng CUI
School of Information Science & Engineering,Shenyang University of Technology Shenyang ,China
国际会议
秦皇岛
英文
303-306
2010-11-05（万方平台首次上网日期，不代表论文的发表时间）