【免费】OpenCV轻松入门-笔记1资源-CSDN文库

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目录（笔记：https://github.com/dhwgithub/Graduate_Study_Notes） 
概念概述........................................................................................................................................... 4 
图像的基本表示方法 ............................................................................................................... 4 
像素处理 ................................................................................................................................... 4 
ROI ............................................................................................................................................. 5 
通道操作 ................................................................................................................................... 6 
获取图像属性 ........................................................................................................................... 6 
图像运算 ................................................................................................................................... 6 
位平面分解 ............................................................................................................................... 7 
图像加密与解密 ..................................................................................................................... 11 
数字水印 ................................................................................................................................. 11 
色彩空间概述 ......................................................................................................................... 13 
alpha 通道 ............................................................................................................................... 14 
仿射......................................................................................................................................... 15 
透视......................................................................................................................................... 15 
重映射..................................................................................................................................... 15 
阈值处理 ................................................................................................................................. 15 
图像平滑处理 ......................................................................................................................... 15 
形态学操作 ............................................................................................................................. 16 
图像梯度 ................................................................................................................................. 17 
Canny 边缘检测 ...................................................................................................................... 18 
图像金字塔 ............................................................................................................................. 19 
图像轮廓 ................................................................................................................................. 19 
直方图..................................................................................................................................... 19 
傅里叶变换 ............................................................................................................................. 20 
模板匹配 ................................................................................................................................. 20 
霍夫变换 ................................................................................................................................. 21 
图像分割与提取 ..................................................................................................................... 21 
支持向量机 ............................................................................................................................. 23 
K 均值聚类.............................................................................................................................. 23 
函数详解......................................................................................................................................... 24 
K 均值聚类实例 ...................................................................................................................... 24 
SVM 算法实例 ........................................................................................................................ 25 
KNN 算法实例 ........................................................................................................................ 27 
交互式前景提取：cv2.grabCut(img,  mask,  rect,  bgdModel,  fgdModel,  iterCount[,  …])  → 
None ........................................................................................................................................ 28 
分水岭算法：cv2.watershed(image, markers) → None ........................................................ 29 
标注图像：cv2. connectedComponents(image[,…]) -> retval, labels .................................... 31 
距离变换：cv2.distanceTransform(src, distanceType, maskSize[, …]) → dst ........................ 31 
霍夫圆变换：cv2.HoughCircles(image, method, dp, minDist[,…]) → circles ........................ 32 
概率霍夫变换：cv2.HoughLinesP(image, rho, theta, threshold[,…]) → lines ....................... 34 
霍夫直线变换：cv2.HoughLines(image, rho, theta, threshold[,…]) → lines ......................... 35 
元组打包：zip() ...................................................................................................................... 36 

获取匹配位置集合：where() ................................................................................................ 37 
绘制矩形：cv2.rectangle(img, pt1, pt2, color[, …]) → None ................................................. 38 
模板匹配：cv2.matchTemplate(image, templ, method[, …]) → result ................................. 39 
逆傅里叶变换示例 ................................................................................................................. 42 
计算频谱幅度：cv2.magnitude(x, y[,…]) → magnitude ........................................................ 42 
傅里叶变换：cv2.dft(src[,…]) → dst ...................................................................................... 43 
傅里叶变换 0：numpy.fft.fft2() ............................................................................................. 43 
添加子窗口及显示：matplotlib.pyplot.subplot() ................................................................. 45 
直方图均衡化：cv2.equalizeHist(src[, dst]) → dst ................................................................ 46 
绘制直方图：cv2.calcHist(images, channels, mask, histSize, ranges[,…]) → hist ................. 46 
绘制直方图 2：matplotlib.pyplot.hist(X, BINS) ..................................................................... 47 
获取对象极点位置：.argmin()、.argmax() ........................................................................... 48 
平均颜色及平均灰度：cv2.mean(src[, mask]) → retval ....................................................... 48 
最大最小值及位置：cv2.minMaxLoc(src[, mask]) → minVal, maxVal, minLoc, maxLoc ...... 48 
计算非零数组位置：numpy.nonzero() ................................................................................. 48 
点到轮廓的距离：cv2.pointPolygonTest(contour, pt, measureDist) → retval ...................... 48 
轮廓是否是凸形：cv2.isContourConvex(contour) → retval ................................................. 49 
计算凸缺陷：cv2.convexityDefects(contour, convexhull[, …]) → convexityDefects ............. 49 
计算轮廓凸包：cv2.convexHull(points[,…]) → hull ............................................................... 49 
逼近多边形：cv2.approxPolyDP(curve, epsilon, closed[,…]) → approxCurve....................... 49 
计算最优拟合直线：cv2.fitLine(points, distType, param, reps, aeps[, line]) → line ............ 50 
计算最优拟合椭圆：cv2.fitEllipse(points) → retval ............................................................. 50 
计算最小包围圆形：cv2.minEnclosingCircle(points) → center, radius ................................ 51 
计算最小包围矩形框：cv2.minAreaRect(points) → retval .................................................. 51 
计算轮廓矩形边界：cv2.boundingRect(points) → retval ..................................................... 52 
形状匹配：cv2.matchShapes(contour1, contour2, method, parameter) → retval ............... 52 
Hu 矩值：cv2.HuMoments(m[, hu]) → hu ............................................................................. 52 
计算轮廓长度：cv2.arcLength(curve, closed) → retval ........................................................ 53 
计算轮廓面积：cv2.contourArea(contour[,…]) → retval ...................................................... 53 
矩特征：cv2.moments(array[, binaryImage]) → retval ......................................................... 53 
绘制轮廓：cv2.drawContours(image, contours, contourIdx, color[,…]) → None ................. 54 
查找图像轮廓：cv2.findContours(image, mode, method[,…]) → contours, hierarchy......... 55 
高斯金字塔向上取样：cv2.pyrUp(src[,…]) → dst ................................................................. 56 
高斯金字塔向下取样：cv2.pyrDown(src[,…]) → dst ............................................................ 56 
Canny 边缘检测：cv2.Canny(image, threshold1, threshold2[,…]) → edges ......................... 56 
Laplacian  算子：cv2.Laplacian(src, ddepth[, …]) → dst ........................................................ 56 
Scharr 算子：cv2.Scharr(src, ddepth, dx, dy[,…]) → dst ........................................................ 57 
对参数取绝对值：cv2.convertScaleAbs(src[,…]) → dst ........................................................ 57 
Sobel 算子：cv2.Sobel(src, ddepth, dx, dy[,…]) → dst ........................................................... 57 
构造核函数：cv2.getStructuringElement(shape, ksize[,…]) → retval ................................... 59 
形态学通用：cv2.morphologyEx(src, op, kernel[,…]) → dst ................................................. 59 
膨胀操作：cv2.dilate(src, kernel[,…]) → dst .......................................................................... 60 
腐蚀操作：cv2.erode(src, kernel[,…]) → dst ......................................................................... 60 
自定义卷积核：cv2.filter2D(src, ddepth, kernel[,…]) → dst ................................................. 61 

双边滤波：cv2.bilateralFilter(src, d, sigmaColor, sigmaSpace[,…]) → dst ............................. 61 
中值滤波：cv2.medianBlur(src, ksize[, dst]) → dst ............................................................... 62 
高斯滤波：cv2.GaussianBlur(src, ksize, sigmaX[,…]) → dst ................................................... 62 
方框滤波：cv2.boxFilter(src, ddepth, ksize[,…]) → dst ......................................................... 62 
均值滤波：cv2.blur(src, ksize[,…]) → dst............................................................................... 63 
自适应阈值：cv2.adaptiveThreshold(src,  maxValue,  adaptiveMethod,  thresholdType, 
blockSize, C[,…]) → dst ............................................................................................................ 63 
阈值化：cv2.threshold(src, thresh, maxval, type[,…]) → retval, dst ...................................... 63 
重映射：cv2.remap(src, map1, map2, interpolation[,…]) → dst ........................................... 64 
获取透视转化矩阵：cv2.getPerspectiveTransform(src, dst) → retval .................................. 66 
透视变换：cv2.warpPerspective(src, M, dsize[,…]) → dst ..................................................... 66 
获取转换矩阵：cv2.getAffineTransform(src, dst) → retval ................................................... 66 
获取转换矩阵：cv2.getRotationMatrix2D(center, angle, scale) → retval ............................. 67 
仿射变换：cv2.warpAffine(src, M, dsize[, dst[, flags[, borderMode[, borderValue]]]]) → dst
 ................................................................................................................................................ 67 
图像翻转：cv2.flip(src, flipCode[, dst]) → dst ....................................................................... 68 
图像缩放：cv2.resize(src, dsize[,…]) → dst ........................................................................... 68 
检测特定元素值：cv2.inRange(src, lowerb, upperb[, …]) → dst .......................................... 70 
色彩空间的变换：cv2.cvtColor(src, code[, …]) → dst ........................................................... 70 
读取图像：cv2.imread(filename[, flags]) → retval ................................................................ 71 
显示图像：cv2.imshow(winname, mat) → None .................................................................. 72 
等待按键：cv2.waitKey([delay]) → retval ............................................................................. 72 
保存图像：cv2.imwrite(filename, img[, params]) → retval .................................................. 72 
 