We introduce three new texture features that are based on the morphological scale-space operator known as the sieve. The new features are tested on two databases. The first, the Outex texture database, contains Brodatz-like textures captured under constant illumination, scale and rotation. The second, the Outex natural scene database, contains images of real-world scenes taken under variable conditions. The new features are compared to univariate granulometries, with which they have some similarities, and to the dual-tree complex wavelet transform, local binary patterns and co-occurrence matrices. The features based upon the sieve are shown to have the best overall performance. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Southam, P., & Harvey, R. (2005). Texture granularities. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3617 LNCS, pp. 304–311). https://doi.org/10.1007/11553595_37
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