opencv学习(8):opencv距离转换函数cv::distanceTransform()

对应头文件:

#include <opencv2/imgproc.hpp>

函数功能：

计算源图像的每个像素到最近的零像素的距离。函数 cv::distanceTransform 计算从每个二进制图像像素到最近的零像素的近似或精确距离。对于零图像像素，距离显然为零。

distanceTransform() [1/2]

c++格式

void cv::distanceTransform   (   InputArray      src,OutputArray     dst,OutputArray     labels,int      distanceType,int    maskSize,int    labelType = DIST_LABEL_CCOMP )

python格式:

cv.distanceTransform(    src, distanceType, maskSize[, dst[, dstType]]   ) ->     dst
cv.distanceTransformWithLabels( src, distanceType, maskSize[, dst[, labels[, labelType]]]   ) ->     dst, labels

参数定义:

    src  8-bit, single-channel (binary) source image.----8位单通道二值图像（0-255）dst   Output image with calculated distances. It is a 8-bit or 32-bit floating-point, single-channel image of the same size as src.----计算距离后的输出图像，8位或32位浮点型的单通道图像labels    Output 2D array of labels (the discrete Voronoi diagram). It has the type CV_32SC1 and the same size as src.----标签的二维输出数组distanceType   Type of distance, see DistanceTypesmaskSize Size of the distance transform mask, see DistanceTransformMasks. DIST_MASK_PRECISE is not supported by this variant. In case of the DIST_L1 or DIST_C distance type, the parameter is forced to 3 because a 3×3 mask gives the same result as 5×5 or any larger aperture.----距离变换蒙版的大小，请参阅 DistanceTransformMasks。 此变体不支持 DIST_MASK_PRECISE。 在 DIST_L1 或 DIST_C 距离类型的情况下，该参数被强制为 3，因为 3×3 掩膜给出与 5×5 或任何更大孔径相同的结果。labelType Type of the label array to build, see DistanceTransformLabelTypes. --标签数组的类型

distanceTransform() [2/2]

这是一个重载的成员函数，是为了方便而提供的。它与上述函数的不同之处仅在于它接受的参数。

c++格式：

void cv::distanceTransform   (   InputArray      src,OutputArray     dst,int     distanceType,int    maskSize,int    dstType = CV_32F )

python格式：

cv.distanceTransform(    src, distanceType, maskSize[, dst[, dstType]]   ) ->     dst
cv.distanceTransformWithLabels( src, distanceType, maskSize[, dst[, labels[, labelType]]]   ) ->     dst, labels

参数:

src  8-bit, single-channel (binary) source image.
dst Output image with calculated distances. It is a 8-bit or 32-bit floating-point, single-channel image of the same size as src .
distanceType    Type of distance, see DistanceTypes
maskSize    Size of the distance transform mask, see DistanceTransformMasks. In case of the DIST_L1 or DIST_C distance type, the parameter is forced to 3 because a 3×3 mask gives the same result as 5×5 or any larger aperture.----距离变换蒙版的大小，请参阅 DistanceTransformMasks。 在 DIST_L1 或 DIST_C 距离类型的情况下，该参数被强制为 3，因为 3×3 掩膜给出与 5×5 或任何更大孔径相同的结果。
dstType Type of output image. It can be CV_8U or CV_32F. Type CV_8U can be used only for the first variant of the function and distanceType == DIST_L1. ----输出图像的类型。 它可以是 CV_8U 或 CV_32F。 类型 CV_8U 只能用于函数的第一个变体和 distanceType == DIST_L1。

DistanceTypes

距离变换和 M 估计器的距离类型

DIST_USER

Python: cv.DIST_USER

User defined distance.

自定义类型

DIST_L1

Python: cv.DIST_L1

distance = |x1-x2| + |y1-y2|

坐标绝对值

DIST_L2

Python: cv.DIST_L2

the simple euclidean distance

简单欧拉距离，应该是坐标差的平方求和再开方

DIST_C

Python: cv.DIST_C

distance = max(|x1-x2|,|y1-y2|)

DIST_L12

Python: cv.DIST_L12

L1-L2 metric: distance = 2(sqrt(1+x*x/2) - 1))

强调x方向距离

DIST_FAIR

Python: cv.DIST_FAIR

distance = c^2(|x|/c-log(1+|x|/c)), c = 1.3998

DIST_WELSCH

Python: cv.DIST_WELSCH

distance = c^2/2(1-exp(-(x/c)^2)), c = 2.9846

DIST_HUBER

Python: cv.DIST_HUBER

distance = |x|<c ? x^2/2 : c(|x|-c/2), c=1.345

DistanceTransformMasks

DIST_MASK_3

Python: cv.DIST_MASK_3

mask=3

3*3掩膜

DIST_MASK_5

Python: cv.DIST_MASK_5

mask=5

5*5掩膜

DIST_MASK_PRECISE

Python: cv.DIST_MASK_PRECISE

@meng