connected(spatstat)
connected()所属R语言包：spatstat
Connected components of an image or window
连接部件的图像或窗口
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Finds the topologically-connected clumps of pixels in an image or window.
查找的图像或窗口中的像素的拓扑连接的团块。
用法----------Usage----------
connected(X, background = NA, method="C")
参数----------Arguments----------
参数：X
Image (object of class "im") or window (object of class "owin").
图片（对象类"im"）或窗口（对象类"owin"）。
参数：background
Optional. Treat pixels with this value as being part of the background.
可选。将像素使用这个值作为背景的一部分。
参数：method
String indicating the algorithm to be used. Either "C" or "interpreted". See Details.
字符串，用于指示要使用的算法。无论是"C"或"interpreted"。查看详细信息。
Details
详细信息----------Details----------
This function computes the connected component transform (Rosenfeld and Pfalz, 1966) of a binary image or binary mask. The argument X is first converted into a pixel image with logical values. Then the algorithm identifies the connected components (topologically-connected clumps of pixels) in the foreground.
此函数计算所连接的成分变换的二值图像或二进制掩码（罗森菲尔德和普法尔茨州，1966年）。参数X是先转换成一个像素的图像与逻辑值。然后，该算法识别所连接的设备（拓扑连接的团块像素）前景。
Two pixels belong to the same connected component if they have the value TRUE and if they are neighbours (in the 8-connected sense). This rule is applied repeatedly until it terminates. Then each connected component contains all the pixels that can be reached by stepping from neighbour to neighbour.
两个像素属于同一关连的组件，如果他们的价值TRUE，如果他们是邻居（8通感）。此规则应用于反复，直到终止。然后，每个连接的组件包含了所有的像素可以达到加强从邻居到邻居。
If method="C", the computation is performed by a compiled C language implementation of the classical algorithm of Rosenfeld and Pfalz (1966). If method="interpreted", the computation is performed by an R implementation of the algorithm of Park et al (2000).
如果method="C"，计算是由一个已编译的C语言实现中的经典算法，罗森菲尔德和普法尔茨州（1966年）。如果method="interpreted"，进行由Park等人（2000）的算法的R执行计算。
The result is a factor-valued image, with levels that correspond to the connected components. The Examples show how to extract each connected component as a separate window object.
其结果是一个因子值的图像，对应于所连接的部件的水平。以下示例显示了如何提取每个连接的组件作为一个单独的窗口对象。
值----------Value----------
A pixel image (object of class "im") with factor values. The levels of the factor correspond to the connected components.
像素的图像（类的对象"im"）因子值。因子的水平对应于所连接的组件。
警告----------Warnings----------
It may be hard to distinguish different components in the default plot because the colours of nearby components may be very similar. See the Examples for a randomised colour map.
这可能是很难在默认的图，因为附近的成分可能会非常相似的颜色来区分不同的组件。颜色随机图的例子。
The algorithm for method="interpreted" can be very slow for large images (or images where the connected components include a large number of pixels).
该算法为method="interpreted"可以是非常慢，对于大图像（或其中所连接的组件包括一个大的像素数的图像）。
（作者）----------Author(s)----------
Original <font face="Courier New,Courier" color="#666666"><b>R</b></font> code by Julian Burgos, University of Washington.
Adapted for <span class="pkg">spatstat</span> by
Adrian Baddeley
<a href="mailto:Adrian.Baddeley@csiro.au">Adrian.Baddeley@csiro.au</a>
<a href="http://www.maths.uwa.edu.au/~adrian/">http://www.maths.uwa.edu.au/~adrian/</a>
and Rolf Turner
<a href="mailto:r.turner@auckland.ac.nz">r.turner@auckland.ac.nz</a>
参考文献----------References----------
Fast connected component labeling algorithm using a divide and conquer technique. Pages 373-376 in S.Y. Shin (ed) Computers and Their Applications: Proceedings of the ISCA 15th International Conference on Computers and Their Applications, March 29-31, 2000, New Orleans, Louisiana USA. ISCA 2000, ISBN 1-880843-32-3.
Sequential operations in digital processing. Journal of the Association for Computing Machinery 13 471-494.
参见----------See Also----------
im.object, tess
im.object，tess
实例----------Examples----------
data(cells)
d <- distmap(cells, dimyx=256)
X <- levelset(d, 0.06)
plot(X)
Z <- connected(X)
plot(Z)
# number of components[的部件数量]
nc <- length(levels(Z))
# plot with randomised colour map[图与随机彩色图]
plot(Z, col=hsv(h=sample(seq(0,1,length=nc), nc)))
# how to extract the components as a list of windows[如何提取组件窗口列表]
W <- tiles(tess(image=Z))
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-9-30 13:19:00
