We propose a similarity measure between two textures based on moments of the Fourier magnitude spectrum. The resulting distance is robust to changes in scale as well as to spatial shifts and grey-scale transforms of the texture samples. This type of invariant distance has applications to content-based image retrieval and classification tasks. We test the performance of the algorithm in a retrieval scenario using texture patches from the Brodatz album. The results indicate that the distance measure emulates human similarity perception in comparing textures.
|Translated title of the contribution||A scale invariant distance measure for texture retrieval|
|Title of host publication||2002 International Conference on Image Processing|
|Publisher||Institute of Electrical and Electronics Engineers (IEEE)|
|Pages||424 - 428|
|Number of pages||4|
|Publication status||Published - Sep 2002|
|Event||International Conference on Image Processing - Rochester, New York, United States|
Duration: 1 Sep 2002 → …
|Conference||International Conference on Image Processing|
|City||Rochester, New York|
|Period||1/09/02 → …|
Bibliographical noteRose publication type: Conference contribution
Sponsorship: This work was supported by EPSRC grant number GR/M84183, under the Link project Autoarch.
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