數(shù)字圖像處理外文翻譯---數(shù)字圖像處理-其他專業(yè)-文庫吧資料
2025-01-27 11:49本頁面
【正文】 數(shù)字圖像處理 1引言 許多研究者 已提議提出了 在數(shù)字圖像里的 連接組件 是 由一個(gè)減少的數(shù)據(jù)量或 簡化的形狀。m+ 1) = 0 ， mi(l) = int((oi(l) ? ei(l)=2)+ oi(l) ， The result of scanning row i is a set of coordinates (i。 j) = 1 6 ^ I(i。 j ? 1) = 0 in row i, counting from the left, with I(i。 T(p)) of the transformed image, and it is not necessarily connected. \Critical Points Algorithms The simplest category of these algorithms determines the midpoints of subsets of connected ponents in standard scan order for each row. Let l be an index for the number of connected ponents in one row of the original image. We de_ne the following functions for 1 _ i _ n: ei(l) = _ j if this is the lth case I(i。 j) = T_(i。 T___(i。 T___(i + 1。 j)) = maxfT__(i。 j。 T__(i。 T__(i ? 1。 j)) = maxfT_(i。 j。 T__(i。 j) = g2(i。 T_(i。 j) = g1(i。 j) let T_(i。 j)) has a value in T equal to T(i。 T(i。 j)] : 1 _ i _ n ^ 1 _ j _ mg, and let T_ _ T such that [(i。 j)。 T(i。 T(i+ 1。 j)) = minfI_(i。 j。 j ? 1) + 1g if I(i。 j)+ 1。 j)) = 8: 0 if I(i。 j。 I_(i。 j) = f2(i。 I(i。 j) = f1(i。 pn = q with pi is a 4neighbor of pi?1, 1 _ i _ n. If p = q the distance between them is de_ned to be zero. The distance d4(p。 p2。 pn = q such that pi is an _neighbor of pi?1, for 1 _ i _ n, and all points on this sequence are either in M or all in the plement of M. A subset M _ C of an image carrier is called _connected i_ M is not empty and all points in M are pairwise _connected with respect to set M. An _ponent of a subset S of C is a maximal _connected subset of S. The study of connectivity in digital images has been introduced in [15]. It follows that any set hIi consists of a number of _ponents. In case of the grid cell model, a ponent is the union of closed squares (2D case) or closed cubes (3D case). The boundary of a 2cell is the union of its four edges and the boundary of a 3cell is the union of its six faces. For practical purposes it is easy to use neighborhood operations (called local operations) on a digital image I which de_ne a value at p 2 C in the transformed image based on pixel 4 values in I at p 2 C and its immediate neighbors in N_(p). 2 Noniterative Algorithms Noniterative algorithms deliver subsets of ponents in specied scan orders without testing connectivity preservation in a number of iterations. In this section we only use the grid point model. \Distance Skeleton Algorithms Blum [3] suggested a skeleton representation by a set of symmetric a closed subset of the Euclidean plane a point p is called symmetric i_ at least 2 points exist on the boundary with equal distances to p. For every symmetric point, the associated maximal disc is the largest disc in this set. The set of symmetric points, each labeled with the radius of the associated maximal disc, constitutes the skeleton of the set. This idea of presenting a ponent of a digital image as a \distance skeleton is based on the calculation of a speci_ed distance from each point in a connected subset M _ C to the plement of the subset. The local maxima of the subset represent a \distance skeleton. In [15] the d4distance is specied as follows. De_nition 1 The distance d4(p。 p2。 q 2 C are _connected with respect to M _ C and neighborhood relation N_ i_ there is a sequence of points p = p0。 j。 j are integers and n。 j), with 1 _ i _ n and 1 _ j _ m。 18。 4。 1。 :::Gmaxg with Gmax _ 1. The range of a binary image is f0。 pn = q such that pi is a neighbor of pi?1, 1 _ i _ n, and p = q. A digital curve is called simple if each point pi has exactly two neighbors in this curve. A digital arc is a subset of a digital curve such tha
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