cv::dilate()是 OpenCV 中用于图像形态学变换的函数之一,与cv::erode()相对,它执行图像的膨胀操作。膨胀是一种将图像中的前景(白色区域)扩展的操作,通常用于填补图像中的小孔洞、连接分离的物体、或增强图像中的亮区域。 1. 函数定义 voidcv::dilate( InputArray src, OutputArray dst, InputArray kernel, Point...
结果捣鼓半天，倒给python2.x装上cv2了，而python3里import cv2则一直失败。
kernel = np.ones((3, 3), np.uint8)dilated_image = cv2.dilate(binary_image, kernel, iterations=1)eroded_image = cv2.erode(binary_image, kernel, iterations=1)stroke_width_map = dilated_image-eroded_imagestroke_width_mean = np.mean(stroke_width_map)stroke_width_std = np.std(stroke_...
image)kernel=np.ones((3,3),np.uint8)#(2,2)表示腐蚀的核大小,就是腐蚀的半径erosion=cv.erode(image,kernel,iterations=1)#iterations=1表示腐蚀的次数cv_show("fushi-eff",erosion)dige_dilate=cv.dilate(erosion,kernel,iterations=1)cv_show('dilate',dige_dilate)...
第三个参数为标识符,可选择MORPH_ERODE、MORPH_DILATE、MORPH_OPEN、MORPH_CLOSE、MORPH_TOPHAT、MORPH_BLACKHAT、MORPH_GRADIENT,以实现上述所有形态学运算。 第四个参数为卷积核,如果输入NULL的话则默认使用3×3矩形卷积核,通常情况下会搭配getStructuringElement()来获得这一参数; ...
# Harris角点检测 harris_corners = cv2.cornerHarris(gray_image, 2, 3, 0.04) # 归一化和显示结果 harris_corners = cv2.dilate(harris_corners, None) color_image[harris_corners > 0.01 * harris_corners.max()] = [0, 0, 255] cv2.imshow('Harris Corners', color_image) cv2.waitKey(0) cv2....
dilate(binary_image, kernel, iterations=1) eroded_image = cv2.erode(binary_image, kernel, iterations=1) stroke_width_map = dilated_image - eroded_image stroke_width_mean = np.mean(stroke_width_map) stroke_width_std = np.std(stroke_width_map) features.extend([stroke_width_mean, stroke_...
dst=dilate(src,element): dst(x,y)=max((x',y') in element))src(x+x',y+y') 函数支持(in-place)模式。膨胀可以重复进行 (iterations) 次. 对彩色图像,每个彩色通道单独处理。 MorphologyEx 高级形态学变换 void cvMorphologyEx( const CvArr* src, CvArr* dst, CvArr* temp, IplConvKernel* eleme...
dilate(binary_image, kernel, iterations=1) eroded_image = cv2.erode(binary_image, kernel, iterations=1) stroke_width_map = dilated_image - eroded_image stroke_width_mean = np.mean(stroke_width_map) stroke_width_std = np.std(stroke_width_map) features.extend([stroke_width_mean, stroke_...
CV::VARP x = _Const(img.data(), {1,11,13,1}, CV::NHWC);automnn_dila_ele = CV::getStructuringElement(0,{2,2});automnn_dilation_map = CV::dilate(x,mnn_dila_ele); cv::Mattbit_map(11,13, CV_32FC1, img.data());