Translator Disclaimer
17 December 1998 Comparing texture feature sets for retrieving core images in petroleum applications
Author Affiliations +
In this paper, the performance of similarity retrieval from a database of earth core images by using different sets of spatial and transformed-based texture features is evaluated and compared. A benchmark consisting of 69 core images from rock samples is devised for the experiments. We show that the Gabor feature set is far superior to other feature sets in terms of precision-recall for the benchmark images. This is in contrast to an earlier report by the authors in which we have observed that the spatial-based feature set outperforms the other feature sets by a wide margin for a benchmark image set consisting of satellite images when the evaluation window has to be small (32 X 32) in order to extract homogenous regions. Consequently, we conclude that optimal texture feature set for texture feature-based similarity retrieval is highly application dependent, and has to be carefully evaluated for each individual application scenario.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Chung-Sheng Li, John R. Smith, Vittorio Castelli, and Lawrence D. Bergman "Comparing texture feature sets for retrieving core images in petroleum applications", Proc. SPIE 3656, Storage and Retrieval for Image and Video Databases VII, (17 December 1998);


The remote sensing image retrieval based on multi-feature
Proceedings of SPIE (October 16 2013)
Video and image clustering using relative entropy
Proceedings of SPIE (December 16 1998)
Image categorization using N x M grams
Proceedings of SPIE (January 14 1997)
Indexing and retrieval in large satellite image databases
Proceedings of SPIE (November 13 2007)

Back to Top