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

对应头文件:

#include 

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 DistanceTypes
    maskSize	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|

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