In this paper we propose a novel interest operator robust to photometric and geometric transformations. Our operator is closely related to the grayscale MSER but it works on the HSV color space, as opposed to the most popular operators in the literature, which are intensity based. It combines a fine and a coarse overlapped quantization of the HSV color space to find maximally stable extremal regions on each of its components and combine them into a final set of regions that are useful in images where intensity does not discriminate well. We evaluate the performance of our operator on two different applications: wide-baseline stereo matching and image annotation. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Penas, M., & Shapiro, L. G. (2009). A color-based interest operator. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5716 LNCS, pp. 965–974). https://doi.org/10.1007/978-3-642-04146-4_103
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