Title :
Multiscale Fourier descriptor for shape-based image retrieval
Author :
Kunttu, Iivari ; Lepistö, Leena ; Rauhamaa, Juhani ; Visa, Ari
Author_Institution :
Inst. of Signal Process., Tampere Univ. of Technol., Finland
Abstract :
The shapes occurring in the images are important in the content-based image retrieval. We introduce a new Fourier-based descriptor for the characterization of the shapes for retrieval purposes. This descriptor combines the benefits of the wavelet transform and Fourier transform. This way the Fourier descriptors can be presented in multiple scales, which improves the shape retrieval accuracy of the commonly used Fourier-descriptors. The multiscale Fourier descriptor is formed by applying the complex wavelet transforms to the boundary function of an object extracted from an image. After that, the Fourier transform is applied to the wavelet coefficients in multiple scales. This way the multiscale shape representation can be expressed in a rotation invariant form. The retrieval efficiency of this multiscale Fourier descriptor is compared to an ordinary Fourier descriptor and CSS-shape representation.
Keywords :
Fourier transforms; content-based retrieval; image representation; image retrieval; wavelet transforms; Fourier transform; content-based image retrieval; multiscale Fourier descriptor; object extraction; shape-based image retrieval; wavelet coefficient; wavelet transform; Content based retrieval; Discrete wavelet transforms; Fourier transforms; Image analysis; Image retrieval; Information retrieval; Shape; Signal processing; Wavelet coefficients; Wavelet transforms;
Conference_Titel :
Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on
Print_ISBN :
0-7695-2128-2
DOI :
10.1109/ICPR.2004.1334371