Spatial frequency channels and perceptual grouping in texture segregation
Computer Vision, Graphics, and Image Processing - Special issue on human and machine vission, part II
Color matching for image retrieval
Pattern Recognition Letters
Design of a two-stage content-based image retrieval system using texture similarity
Information Processing and Management: an International Journal
Texture image retrieval using rotated wavelet filters
Pattern Recognition Letters
Texture image retrieval using new rotated complex wavelet filters
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Rotation-Invariant Texture Image Retrieval Using Rotated Complex Wavelet Filters
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Statistical texture characterization from discrete wavelet representations
IEEE Transactions on Image Processing
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During the last decades, several approaches were proposed to describe texture contents of an image. In early research works, the texture features were mainly extracted from the pixel space itself (Edge histograms, Co-occurrence-based features). Later on, the focus was more on the use of dual spaces (transform of pixel space) such as frequency space or spaces resulting from Gabor and wavelet transforms. Recent physiological studies showed that the human visual system can be modeled as a set of independent channels of various orientations and scales, this finding motivated the proliferation of multi-resolution methods for describing texture images. Most of these methods are either wavelet-based or Gabor-based. In this paper we propose a multi-resolution technique for characterizing and retrieving images which works on the Fourier domain. Our approach differs from the work of [3] since it applies global Fourier transform on a hierarchy of images of various resolutions while their approach uses local (windowed) Fourier transform of increasing sizes. The experiments we have conducted showed that the multi-resolution approach improves the retrieval accuracy of the similar method that uses the same texture feature vector but in a single resolution. The experiments have also demonstrated that our Fourier based multi-resolution technique outperforms many wavelet-based multi-resolution techniques recently described in literature.