opencv 骨架提取/图片细化代码

其实在opencv里面是有骨架提取的代码的
只不过是在扩展模块opencv-contrib

void cv::ximgproc::thinning  (   InputArray  src,OutputArray     dst,int     thinningType = THINNING_ZHANGSUEN
)

其代码介绍为

Applies a binary blob thinning operation, to achieve a skeletization of the input image.
(应用于腌摸细化操作，从而实现对输入图像的骨架提取)
The function transforms a binary blob image into a skeletized form using the technique of Zhang-Suen.
(这个函数是使用Zhang-Suen的技术实现从腌摸到骨架的转换)

Parameters

src Source 8-bit single-channel image, containing binary blobs, with blobs having 255 pixel values.
dst Destination image of the same size and the same type as src. The function can work in-place.
thinningType Value that defines which thinning algorithm should be used. See cv::ximgproc::ThinningTypes

但是想一想如果只想要这一个功能，编译那么多是挺麻烦的
作为一名代码搬运工，我就从里面扣出来了这一段

enum thinningType{THINNING_ZHANGSUEN,THINNING_GUOHALL
};
// Applies a thinning iteration to a binary image
static void thinningIteration(Mat img, int iter, int thinningType){Mat marker = Mat::zeros(img.size(), CV_8UC1);if(thinningType == THINNING_ZHANGSUEN){for (int i = 1; i < img.rows-1; i++){for (int j = 1; j < img.cols-1; j++){uchar p2 = img.at<uchar>(i-1, j);uchar p3 = img.at<uchar>(i-1, j+1);uchar p4 = img.at<uchar>(i, j+1);uchar p5 = img.at<uchar>(i+1, j+1);uchar p6 = img.at<uchar>(i+1, j);uchar p7 = img.at<uchar>(i+1, j-1);uchar p8 = img.at<uchar>(i, j-1);uchar p9 = img.at<uchar>(i-1, j-1);int A  = (p2 == 0 && p3 == 1) + (p3 == 0 && p4 == 1) +(p4 == 0 && p5 == 1) + (p5 == 0 && p6 == 1) +(p6 == 0 && p7 == 1) + (p7 == 0 && p8 == 1) +(p8 == 0 && p9 == 1) + (p9 == 0 && p2 == 1);int B  = p2 + p3 + p4 + p5 + p6 + p7 + p8 + p9;int m1 = iter == 0 ? (p2 * p4 * p6) : (p2 * p4 * p8);int m2 = iter == 0 ? (p4 * p6 * p8) : (p2 * p6 * p8);if (A == 1 && (B >= 2 && B <= 6) && m1 == 0 && m2 == 0)marker.at<uchar>(i,j) = 1;}}}if(thinningType == THINNING_GUOHALL){for (int i = 1; i < img.rows-1; i++){for (int j = 1; j < img.cols-1; j++){uchar p2 = img.at<uchar>(i-1, j);uchar p3 = img.at<uchar>(i-1, j+1);uchar p4 = img.at<uchar>(i, j+1);uchar p5 = img.at<uchar>(i+1, j+1);uchar p6 = img.at<uchar>(i+1, j);uchar p7 = img.at<uchar>(i+1, j-1);uchar p8 = img.at<uchar>(i, j-1);uchar p9 = img.at<uchar>(i-1, j-1);int C  = ((!p2) & (p3 | p4)) + ((!p4) & (p5 | p6)) +((!p6) & (p7 | p8)) + ((!p8) & (p9 | p2));int N1 = (p9 | p2) + (p3 | p4) + (p5 | p6) + (p7 | p8);int N2 = (p2 | p3) + (p4 | p5) + (p6 | p7) + (p8 | p9);int N  = N1 < N2 ? N1 : N2;int m  = iter == 0 ? ((p6 | p7 | (!p9)) & p8) : ((p2 | p3 | (!p5)) & p4);if ((C == 1) && ((N >= 2) && ((N <= 3)) & (m == 0)))marker.at<uchar>(i,j) = 1;}}}img &= ~marker;
}// Apply the thinning procedure to a given image
void thinning(InputArray input, OutputArray output, int thinningType){Mat processed = input.getMat().clone();// Enforce the range of the input image to be in between 0 - 255processed /= 255;Mat prev = Mat::zeros(processed.size(), CV_8UC1);Mat diff;do {thinningIteration(processed, 0, thinningType);thinningIteration(processed, 1, thinningType);absdiff(processed, prev, diff);processed.copyTo(prev);}while (countNonZero(diff) > 0);processed *= 255;output.assign(processed);
}

之后就复制粘贴到自己的代码里用吧

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