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An ordinal co-occurrence matrix framework for texture retrieval

Research output: Contribution to journalArticleScientificpeer-review


Original languageEnglish
Pages (from-to)15 p
JournalEurasip Journal on Image and Video Processing
Publication statusPublished - 2007
Publication typeA1 Journal article-refereed


We present a novel ordinal co-occurrence matrix framework for the purpose of content-based texture retrieval. Several particularizations of the framework will be derived and tested for retrieval purposes. Features obtained using the framework represent the occurrence frequency of certain ordinal relationships at different distances and orientations. In the ordinal co-occurrence matrix framework, the actual pixel values do not affect the features, instead, the ordinal relationships between the pixels are taken into account. Therefore, the derived features are invariant to monotonic gray-level changes in the pixel values and can thus be applied to textures which may be obtained, for example, under different illumination conditions. Described ordinal co-occurrence matrix approaches are tested and compared against other well-known ordinal and nonordinal methods.

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