Texture Retrieval with Descriptors Based on Local Fourier Transform: Comparing the Rectangular and Circular Neighbourhoods
نویسندگان
چکیده
The texture descriptors derived from 1-D DFT (Discrete Fourier Transform) of the pixel values of a local neighbourhood have been shown to perform better than the methods based on wavelets for image retrieval and recognition. These DFT-based texture descriptors were extracted from rectangular or circular neighbourhoods. This paper compares the texture descriptors extracted from rectangular and the circular neighbourhoods previously proposed in the literature. A database of images is constructed from Brodatz album and the texture descriptors extracted from the two types of neighbourhoods are compared for texture retrieval. This paper shows that extracting DFT-based features from circular neighbourhood is almost thrice as expensive as extracting the same from the rectangular neighbourhood. The results of image retrieval on a large image database show that the descriptor extracted from rectangular neighbourhoods performs better than the same extracted from the circular neighbourhoods.
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