Zhang-Suen 图像骨架提取算法的原理和OpenCV实现

记录一下图像骨架提取算法，转载至 两种图像骨架提取算法的研究(1)原理部分

基于OpenCV的实现代码如下，代码部分参考 opencv骨架提取/图像细化

void thinImage(Mat & srcImg) {vector<Point> deleteList;int neighbourhood[9];int nl = srcImg.rows;int nc = srcImg.cols;bool inOddIterations = true;while (true) {for (int j = 1; j < (nl - 1); j++) {uchar* data_last = srcImg.ptr<uchar>(j - 1);uchar* data = srcImg.ptr<uchar>(j);uchar* data_next = srcImg.ptr<uchar>(j + 1);for (int i = 1; i < (nc - 1); i++) {if (data[i] == 255) {int whitePointCount = 0;neighbourhood[0] = 1;if (data_last[i] == 255) neighbourhood[1] = 1;else  neighbourhood[1] = 0;if (data_last[i + 1] == 255) neighbourhood[2] = 1;else  neighbourhood[2] = 0;if (data[i + 1] == 255) neighbourhood[3] = 1;else  neighbourhood[3] = 0;if (data_next[i + 1] == 255) neighbourhood[4] = 1;else  neighbourhood[4] = 0;if (data_next[i] == 255) neighbourhood[5] = 1;else  neighbourhood[5] = 0;if (data_next[i - 1] == 255) neighbourhood[6] = 1;else  neighbourhood[6] = 0;if (data[i - 1] == 255) neighbourhood[7] = 1;else  neighbourhood[7] = 0;if (data_last[i - 1] == 255) neighbourhood[8] = 1;else  neighbourhood[8] = 0;for (int k = 1; k < 9; k++) {whitePointCount += neighbourhood[k];}if ((whitePointCount >= 2) && (whitePointCount <= 6)) {int ap = 0;if ((neighbourhood[1] == 0) && (neighbourhood[2] == 1)) ap++;if ((neighbourhood[2] == 0) && (neighbourhood[3] == 1)) ap++;if ((neighbourhood[3] == 0) && (neighbourhood[4] == 1)) ap++;if ((neighbourhood[4] == 0) && (neighbourhood[5] == 1)) ap++;if ((neighbourhood[5] == 0) && (neighbourhood[6] == 1)) ap++;if ((neighbourhood[6] == 0) && (neighbourhood[7] == 1)) ap++;if ((neighbourhood[7] == 0) && (neighbourhood[8] == 1)) ap++;if ((neighbourhood[8] == 0) && (neighbourhood[1] == 1)) ap++;if (ap == 1) {if (inOddIterations && (neighbourhood[3] * neighbourhood[5] * neighbourhood[7] == 0)&& (neighbourhood[1] * neighbourhood[3] * neighbourhood[5] == 0)) {deleteList.push_back(Point(i, j));}else if (!inOddIterations && (neighbourhood[1] * neighbourhood[5] * neighbourhood[7] == 0)&& (neighbourhood[1] * neighbourhood[3] * neighbourhood[7] == 0)) {deleteList.push_back(Point(i, j));}}}}}}if (deleteList.size() == 0)break;for (size_t i = 0; i < deleteList.size(); i++) {Point tem;tem = deleteList[i];uchar* data = srcImg.ptr<uchar>(tem.y);data[tem.x] = 0;}deleteList.clear();inOddIterations = !inOddIterations;}
}

原图和细化结果如下：

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