| has gloss | eng: Structure tensors (or second-moment matrices) are matrix representations of partial derivatives. In the field of image processing and computer vision, they are typically used to represent gradients, edges or similar information. Structure tensors also provide a more powerful description of local patterns when compared with the directional derivative through its coherence measure. They have several other advantages that are detailed in the structure tensor section of this tutorial. This article is written largely from the point of view of image processing applications; however, it should also be useful to those from a more general math background who want to learn more about this representation. |
