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Blur robust and color constant image description

Joost van de Weijer 1 Cordelia Schmid 1, *
* Corresponding author
1 LEAR - Learning and recognition in vision
GRAVIR - IMAG - Laboratoire d'informatique GRAphique, VIsion et Robotique de Grenoble, Inria Grenoble - Rhône-Alpes, CNRS - Centre National de la Recherche Scientifique : FR71
Abstract : An important class of color constant image descriptors is based on image derivatives. These derivative-based image descriptors have a major drawback: they are sensitive to changes of image blur. Image blur has various causes such as being out-of-focus, motion of the camera or the object, and inaccurate acquisition settings. Since image blur is a frequently occurring image degradation, it is desirable for object description to be robust to its variations. We propose a set of descriptors which are both robust with respect to blurring effects, and invariant to illuminant color changes. Experiments on retrieval tasks show that the newly proposed object descriptors outperform existing descriptors in the presence of blurring effects.
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Joost van de Weijer, Cordelia Schmid. Blur robust and color constant image description. International Conference on Image Processing (ICIP '06), Oct 2006, Atlanta, United States. pp.993--996, ⟨10.1109/ICIP.2006.312666⟩. ⟨inria-00548575⟩

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