（三）OpenCV图像处理-透视校正技术。

简介：
由于拍摄或扫描的图像通常并非规则矩形，这会对后续的图像处理步骤造成负面影响，因此需要借助透视变换技术对其进行校正，从而获得准确的几何形状。具体而言，通过二值分割、形态学方法、Hough直线检测以及透视变换等一系列处理，可以有效地修正图像的形状问题。 #include #include using namespace std; using namespace cv; RNG rng; int main(int argc, char** argv) { Mat src, temp_threshold, temp_mor, temp_contours, temp_hough, dst; src = imread(../path.jpg); if (src.empty()) { cout << Could not open or find the image << endl; return -1; } // Convert to grayscale cvtColor(src, src, COLOR_BGR2GRAY); // Apply thresholding to obtain a binary image threshold(src, temp_threshold, 0, 255, THRESH_BINARY | THRESH_OTSU); // Apply morphological operations (e.g., opening and closing) to refine the binary image morphologyEx(temp_threshold, temp_mor, MORPH_OPEN, Mat(), 3, 3); // Opening operation for noise removal and small hole filling. Adjust kernel size as needed. // Find contours in the binary image findContours(temp_mor, temp_contours, RETR_EXTERNAL | RETR_TREE, CHAIN_APPROX_SIMPLE); // Detect lines using the Hough transform. Adjust parameters as needed for your specific images. vector lines; // Store detected lines. This is where the Hough transform results are stored. HoughLinesP(temp_mor, temp_hough, 10000 , 1 , 0 , vector(), Vec4i(), DETECT_PRIMARY_ALTUS); // Apply perspective transform to correct the shape of the object/image Mat homography = getPerspectiveTransform(Mat(cv::Point2f(0.,0.) , cv::Point2f(src.cols , src.rows)), Mat()); warpPerspective(src , dst , homography , src.size()); }