- 二值图像
- 完整源码
- 效果
- 原图
- 腐蚀运算
- 膨胀运算
- 开运算
- 闭运算
- 灰度图像
- 完整源码
- 效果
- 原图
- 腐蚀运算
- 膨胀运算
- 开运算
- 闭运算
平台:Windows 10 20H2
Visual Studio 2015
OpenCV 4.5.3
二值图像 完整源码
//包含头文件 #include效果 原图 腐蚀运算 膨胀运算 开运算 闭运算 灰度图像 完整源码//命名空间 using namespace cv; using namespace std; //全局函数声明部分 //我的腐蚀运算 Mat Erode(Mat src, Mat Mask, uint32_t x0, uint32_t y0) { uint32_t x = 0, y = 0; Mat dst(src.rows, src.cols, CV_8U, Scalar(0)); for (x = 0; x < src.cols; ++x) { for (y = 0; y < src.rows; ++y) { //确定是否需要腐蚀 uint8_t dst_P = 1; for (uint32_t xm = 0; xm < Mask.cols; ++xm) { for (uint32_t ym = 0; ym < Mask.rows; ++ym) { if (dst_P && Mask.at (Point(xm, ym)) && (x + xm - x0) < src.cols && (y + ym - y0) < src.rows) dst_P &= (Mask.at (Point(xm, ym)) & src.at (Point(x + xm - x0, y + ym - y0))); } if (!dst_P) break; } if (dst_P) dst.at (Point(x, y)) = src.at (Point(x, y)); else dst.at (Point(x, y)) = 0; //腐蚀 } } return dst; } //我的膨胀运算 Mat Dilate(Mat src, Mat Mask, uint32_t x0, uint32_t y0) { uint32_t x = 0, y = 0; Mat dst(src.rows, src.cols, CV_8U, Scalar(0)); for (x = 0; x < src.cols; ++x) { for (y = 0; y < src.rows; ++y) { //确定是否需要膨胀 uint8_t dst_P = 0; for (uint32_t xm = 0; xm < Mask.cols; ++xm) { for (uint32_t ym = 0; ym < Mask.rows; ++ym) { if (!dst_P && Mask.at (Point(xm, ym)) && (x + xm - x0) < src.cols && (y + ym - y0) < src.rows) dst_P |= src.at (Point(x + xm - x0, y + ym - y0)); } if (dst_P) break; } for (uint32_t xm = 0; xm < Mask.cols; ++xm) { for (uint32_t ym = 0; ym < Mask.rows; ++ym) { if ((x + xm - x0) < src.cols && (y + ym - y0) < src.rows) if (dst_P) dst.at (Point(x + xm - x0, y + ym - y0)) = 255; //膨胀 else dst.at (Point(x + xm - x0, y + ym - y0)) = src.at (Point(x, y)); } } } } return dst; } //主函数 int main(int argc, char * argv[]) { //【1】载入图像,灰度化 Mat image = imread("D:\Work\OpenCV\Workplace\Test_1\2.jpg", 0);//灰度原图 //【2】检查是否载入成功 if (image.empty()) { printf("读取图片错误,请确认目录下是否有imread函数指定图片存在!n"); return 0; } //【3】阈值化生成二值图像 Mat binaryImage; threshold(image, binaryImage, 127, 255, THRESH_BINARY); //【4】生成结构元素 uint8_t element_a[3][3] = { 1, 1, 1, 1, 1, 1, 1, 1, 1, }; Mat element = Mat(sizeof(element_a)/sizeof(element_a[0]), sizeof(element_a[0])/element_a[0][0], CV_8U, element_a); //【5】显示图像 imshow("原二值图像", binaryImage); //【6】腐蚀运算 Mat erodedImage; erode(binaryImage, erodedImage, element); imshow("Opencv的腐蚀运算", erodedImage); imshow("我的腐蚀运算", Erode(binaryImage, element, 1, 1)); //【7】膨胀运算 Mat dilatedImage; dilate(binaryImage, dilatedImage, element); imshow("Opencv的膨胀运算", dilatedImage); imshow("我的膨胀运算", Dilate(binaryImage, element, 1, 1)); //【8】开运算 Mat OpenImage; morphologyEx(binaryImage, OpenImage, MORPH_OPEN, element); imshow("Opencv的开运算", OpenImage); imshow("我的开运算", Dilate(Erode(binaryImage, element, 1, 1), element, 1, 1)); //开运算即先腐蚀再膨胀 //【9】闭运算 Mat CloseImage; morphologyEx(binaryImage, CloseImage, MORPH_CLOSE, element); imshow("Opencv的闭运算", CloseImage); imshow("我的闭运算", Erode(Dilate(binaryImage, element, 1, 1), element, 1, 1)); //闭运算即先膨胀再腐蚀 //【10】保持窗口显示 waitKey(0); return 0; }
//包含头文件 #include效果 原图 腐蚀运算//命名空间 using namespace cv; using namespace std; //全局函数声明部分 //我的腐蚀运算 Mat Erode(Mat src, Mat Mask, uint32_t x0, uint32_t y0) { uint32_t x = 0, y = 0; Mat dst(src.rows, src.cols, CV_8U, Scalar(0)); for (x = 0; x < src.cols; ++x) { for (y = 0; y < src.rows; ++y) { uint8_t dst_P = 255; for (uint32_t xm = 0; xm < Mask.cols; ++xm) { for (uint32_t ym = 0; ym < Mask.rows; ++ym) { if (dst_P && Mask.at (Point(xm, ym)) && (x + xm - x0) < src.cols && (y + ym - y0) < src.rows) if (dst_P > src.at (Point(x + xm - x0, y + ym - y0))) //寻找最小值 dst_P = src.at (Point(x + xm - x0, y + ym - y0)); } if (!dst_P) break; } dst.at (Point(x, y)) = dst_P; } } return dst; } //我的膨胀运算 Mat Dilate(Mat src, Mat Mask, uint32_t x0, uint32_t y0) { uint32_t x = 0, y = 0; Mat dst(src.rows, src.cols, CV_8U, Scalar(0)); for (x = 0; x < src.cols; ++x) { for (y = 0; y < src.rows; ++y) { uint8_t dst_P = 0; for (uint32_t xm = 0; xm < Mask.cols; ++xm) { for (uint32_t ym = 0; ym < Mask.rows; ++ym) { if (dst_P != 255 && Mask.at (Point(xm, ym)) && (x + xm - x0) < src.cols && (y + ym - y0) < src.rows) if (dst_P < src.at (Point(x + xm - x0, y + ym - y0))) //寻找最大值 dst_P = src.at (Point(x + xm - x0, y + ym - y0)); } if (dst_P == 255) break; } dst.at (Point(x, y)) = dst_P; } } return dst; } //主函数 int main(int argc, char * argv[]) { //【1】载入图像,灰度化 Mat image = imread("D:\Work\OpenCV\Workplace\Test_1\8.jpg", 0);//灰度原图 //【2】检查是否载入成功 if (image.empty()) { printf("读取图片错误,请确认目录下是否有imread函数指定图片存在!n"); return 0; } //【3】生成结构元素 uint8_t element_a[7][7] = { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, }; Mat element = Mat(sizeof(element_a)/sizeof(element_a[0]), sizeof(element_a[0])/element_a[0][0], CV_8U, element_a); //【4】显示图像 imshow("原灰度图像", image); //【5】腐蚀运算 Mat erodedImage; erode(image, erodedImage, element); imshow("Opencv的腐蚀运算", erodedImage); imshow("我的腐蚀运算", Erode(image, element, 3, 3)); //【6】膨胀运算 Mat dilatedImage; dilate(image, dilatedImage, element); imshow("Opencv的膨胀运算", dilatedImage); imshow("我的膨胀运算", Dilate(image, element, 3, 3)); //【7】开运算 Mat OpenImage; morphologyEx(image, OpenImage, MORPH_OPEN, element); imshow("Opencv的开运算", OpenImage); imshow("我的开运算", Dilate(Erode(image, element, 3, 3), element, 3, 3)); //开运算即先腐蚀再膨胀 //【8】闭运算 Mat CloseImage; morphologyEx(image, CloseImage, MORPH_CLOSE, element); imshow("Opencv的闭运算", CloseImage); imshow("我的闭运算", Erode(Dilate(image, element, 3, 3), element, 3, 3)); //闭运算即先膨胀再腐蚀 //【10】保持窗口显示 waitKey(0); return 0; }
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