qq_42286035的博客

//构建一个QT的QRect对象QRect qrect(0, 0, 100, 100);qDebug()<<"qrect.bottomRight:"<<qrect.bottomRight();//构建一个opencv的cv::Rect对象cv::Rect rect(0, 0, 100, 100);qDebug()<<"rect.bottomRight:"<<rect.br().x<<","<< rect.br().y;执

//功能：填充区域中的孔//参数：// src：输入图像// dst：输出图像//返回值：无void fill_up(Mat src, Mat &dst){ dst = Mat(src.size(), CV_8UC1, Scalar(0)); vector<vector<Point>> contours; findContours(src, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE

//功能：求图中像素值为255的斑块面积和重心坐标//参数：// src：输入图像// area：图中像素值为255的像素个数// center：斑块的重心坐标//返回值：无void area_center(Mat src, int &area, Point2f &center){ int pixelsCount = src.rows * src.cols; area = 0; center = Point2f(0, 0); float c

enum SortCriterion{ FIRST_POINT, //区域第一行的最左侧的点 LAST_POINT, //区域最后一行的最右侧的点 UPPER_LEFT, //区域周围矩形的左上角 UPPER_RIGHT, //区域周围矩形的右上角 LOWER_LEFT, //区域周围矩形的左下角 LOWER_RIGHT //区域周围矩形的右下角};enum SortDirection{ ROW,.

enum ShapeTransType{ SHAPETRANS_RECTANGLE, //平行于坐标轴的最小外接矩形 SHAPETRANS_CIRCLE, //最小外接圆 SHAPETRANS_CONVER //凸包};void shape_trans(Mat src, Mat &dst, ShapeTransType type){ dst = Mat(src.size(), CV_8UC1, Scalar(0)); vector<vec.

void fast_threshold(Mat src, Mat mask, Mat &dst, int minGray, int maxGray, int minSize){ dst = Mat(src.size(), CV_8UC1, Scalar(0)); if (minSize <= 0 || minSize >= src.rows) return; int rows = src.rows; int cols = src.col.

enum ThresholdType{ THRESHOLD_LIGHT, //明 THRESHOLD_DARK, //暗 THRESHOLD_EQUAL, //等于 THRESHOLD_NOT_EQUAL //不等于};void var_threshold(Mat src, Mat mask, Mat &dst, int maskW, int maskH, float StdDevScale, .

enum ThresholdType{ THRESHOLD_LIGHT, //明 THRESHOLD_DARK, //暗 THRESHOLD_EQUAL, //等于 THRESHOLD_NOT_EQUAL //不等于};void dyn_threshold(Mat src, Mat pre, Mat &dst, int offset, ThresholdType type){ dst = Mat(src.size(), CV_8UC1, .

enum SelectShapeType{ SELECT_AREA, //选中区域面积 SELECT_RECTANGULARITY, //选中区域矩形度 SELECT_WIDTH, //选中区域宽度（平行于坐标轴） SELECT_HEIGHT, //选中区域高度（平行于坐标轴） SELECT_ROW, //选中区域中心行索引 SELECT_COLUMN, //选中区域中心列索引 SELECT_RECT2_LEN1, //选中区域最小外接矩形的一半长度 SELECT.

cv::Mat img = cv::imread("2.bmp"); cv::Mat m1, m2, dst; cv::threshold(img, m1, 70, 255, cv::THRESH_BINARY); cv::threshold(img, m2, 240, 255, cv::THRESH_BINARY_INV); cv::bitwise_and(m1, m2, dst);