【opencv】二值图像细化



139 lines (115 sloc)  3.3 KB

	/**
	* Code for thinning a binary image using Zhang-Suen algorithm.
	*
	* Author:  Nash (nash [at] opencv-code [dot] com)
	* Website: http://opencv-code.com
	*/
	#include <opencv2/opencv.hpp>
	/**
	* Perform one thinning iteration.
	* Normally you wouldn't call this function directly from your code.
	*
	* Parameters:
	* im    Binary image with range = [0,1]
	* iter  0=even, 1=odd
	*/
	void thinningIteration(cv::Mat& img, int iter)
	{
	CV_Assert(img.channels() == 1);
	CV_Assert(img.depth() != sizeof(uchar));
	CV_Assert(img.rows > 3 && img.cols > 3);
	cv::Mat marker = cv::Mat::zeros(img.size(), CV_8UC1);
	int nRows = img.rows;
	int nCols = img.cols;
	if (img.isContinuous()) {
	nCols *= nRows;
	nRows = 1;
	}
	int x, y;
	uchar *pAbove;
	uchar *pCurr;
	uchar *pBelow;
	uchar *nw, *no, *ne;    // north (pAbove)
	uchar *we, *me, *ea;
	uchar *sw, *so, *se;    // south (pBelow)
	uchar *pDst;
	// initialize row pointers
	pAbove = NULL;
	pCurr  = img.ptr<uchar>(0);
	pBelow = img.ptr<uchar>(1);
	for (y = 1; y < img.rows-1; ++y) {
	// shift the rows up by one
	pAbove = pCurr;
	pCurr  = pBelow;
	pBelow = img.ptr<uchar>(y+1);
	pDst = marker.ptr<uchar>(y);
	// initialize col pointers
	no = &(pAbove[0]);
	ne = &(pAbove[1]);
	me = &(pCurr[0]);
	ea = &(pCurr[1]);
	so = &(pBelow[0]);
	se = &(pBelow[1]);
	for (x = 1; x < img.cols-1; ++x) {
	// shift col pointers left by one (scan left to right)
	nw = no;
	no = ne;
	ne = &(pAbove[x+1]);
	we = me;
	me = ea;
	ea = &(pCurr[x+1]);
	sw = so;
	so = se;
	se = &(pBelow[x+1]);
	int A  = (*no == 0 && *ne == 1) + (*ne == 0 && *ea == 1) +
	(*ea == 0 && *se == 1) + (*se == 0 && *so == 1) +
	(*so == 0 && *sw == 1) + (*sw == 0 && *we == 1) +
	(*we == 0 && *nw == 1) + (*nw == 0 && *no == 1);
	int B  = *no + *ne + *ea + *se + *so + *sw + *we + *nw;
	int m1 = iter == 0 ? (*no * *ea * *so) : (*no * *ea * *we);
	int m2 = iter == 0 ? (*ea * *so * *we) : (*no * *so * *we);
	if (A == 1 && (B >= 2 && B <= 6) && m1 == 0 && m2 == 0)
	pDst[x] = 1;
	}
	}
	img &= ~marker;
	}
	/**
	* Function for thinning the given binary image
	*
	* Parameters:
	* src  The source image, binary with range = [0,255]
	* dst  The destination image
	*/
	void thinning(const cv::Mat& src, cv::Mat& dst)
	{
	dst = src.clone();
	dst /= 255;         // convert to binary image
	cv::Mat prev = cv::Mat::zeros(dst.size(), CV_8UC1);
	cv::Mat diff;
	do {
	thinningIteration(dst, 0);
	thinningIteration(dst, 1);
	cv::absdiff(dst, prev, diff);
	dst.copyTo(prev);
	}
	while (cv::countNonZero(diff) > 0);
	dst *= 255;
	}
	/**
	* This is an example on how to call the thinning funciton above
	*/
	int main()
	{
	cv::Mat src = cv::imread("image.png");
	if (!src.data)
	return -1;
	cv::Mat bw;
	cv::cvtColor(src, bw, CV_BGR2GRAY);
	cv::threshold(bw, bw, 10, 255, CV_THRESH_BINARY);
	thinning(bw, bw);
	cv::imshow("src", src);
	cv::imshow("dst", bw);
	cv::waitKey();
	return 0;
	}