翻訳と辞書 Words near each other ・ Orientales Ecclesias ・ Orientales omnes Ecclesias ・ Orientalis ・ Orientalis Ecclesiae ・ Orientalism ・ Orientalism (book) ・ Orientalism in early modern France ・ Orientalist ・ Orientalium ・ Orientalium dignitas ・ Orientalium Ecclesiarum ・ Orientalizing period ・ Orientamenti ・ Orientate ・ Orientation ・ Orientation (computer vision) ・ Orientation (EP) ・ Orientation (geometry) ・ Orientation (graph theory) ・ Orientation (Heroes) ・ Orientation (Lost) ・ Orientation (mental) ・ Orientation (sign language) ・ Orientation (vector space) ・ Orientation and Mobility ・ Orientation camps in Hong Kong ・ Orientation character ・ Orientation column ・ Orientation entanglement ・ Orientation of a vector bundle Dictionary Lists mini英和辞書 mini和英辞書 Webster 1913 Latin-English FOLDOC Wikipedia English ウィキペディア

翻訳と辞書　辞書検索 [ 開発暫定版 ] スポンサード リンク Orientation (computer vision) ： ウィキペディア英語版 Orientation (computer vision) In computer vision and image processing a common assumption is that sufficiently small image regions can be characterized as locally one-dimensional, e.g., in terms of lines or edges. For natural images this assumption is usually correct except at specific points, e.g., corners or line junctions or crossings, or in regions of high frequency textures. However, what size the regions have to be in order to appear as one-dimensional varies both between images and within an image. Also, in practice a local region is never exactly one-dimensional but can be so to a sufficient degree of approximation. Image regions which are one-dimensional are also referred to as simple or intrinsic one-dimensional (i1D). Given an image of dimension d (d = 2 for ordinary images), a mathematical representation of a local i1D image region is $f(\backslash mathbf)\; =\; g(\backslash mathbf\; \backslash cdot\; \backslash hat)$ where $f$ is the image intensity function which varies over a local image coordinate $\backslash mathbf$ (a d-dimensional vector), $g$ is a one-variable function, and $\backslash hat$ is a unit vector. The intensity function $f$ is constant in all directions which are perpendicular to $\backslash hat$. Intuitively, the orientation of an i1D-region is therefore represented by the vector $\backslash hat$. However, for a given $f$, $\backslash hat$ is not uniquely determined. If $\backslash tilde\; =\; -\; \backslash hat$ $\backslash tilde(x)\; =\; g(-x)$ then $f$ can be written as $f(\backslash mathbf)\; =\; \backslash tilde(\backslash mathbf\; \backslash cdot\; \backslash tilde)$ which implies that $\backslash tilde\; =\; -\; \backslash hat$ also is a valid representation of the local orientation. In order to avoid this ambiguity in the representation of local orientation two representations have been proposed * The double angle representation * The tensor representation The double angle representation is only valid for 2D images (d=2), but the tensor representation can be defined for arbitrary dimensions d of the image data. ==Relation to direction== A line between two points p1 and p2 has no given direction, but has a well-defined orientation. However, if one of the points p1 is used as a reference or origin, then the other point p2 can be described in terms of a vector which points in the direction to p2. Intuitively, orientation can be thought of as a direction without sign. Formally, this relates to projective spaces where the orientation of a vector corresponds to the equivalence class of vectors which are scaled versions of the vector. For an image edge, we may talk of its direction which can be defined in terms of the gradient, pointing in the direction of maximum image intensity increase (from dark to bright). This implies that two edges can have the same orientation but the corresponding image gradients point in opposite directions if the edges go in different directions. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Orientation (computer vision)」の詳細全文を読む スポンサード リンク 翻訳と辞書 : 翻訳のためのインターネットリソース Copyright(C) kotoba.ne.jp 1997-2016. All Rights Reserved.