Harris角点检测算法.docx

Harris角点检测：原理:利用矩形窗在图像上移动，若窗内包含有角点，则窗口向各个方向移动时，窗内的灰度值都会发生变化。从而达到检测图像角点的目的。方法：（增大的值，将减小角点响应值R，降低角点检测的灵性，减少被检测角点的数量；减小值，将增大角点响应值R，增加角点检测的灵敏性，增加被检测角点的数量。）算法特点：对亮度和对比度的变化不敏感；具有旋转不变性，但不具有尺度不变性；并不具备仿射不变性；算法实现：void detectHarrisCorners(const Mat& imgSrc, Mat& imgDst, double alpha)Mat gray;if (imgSrc.channels() = 3)cvtColor(imgSrc, gray, CV_BGR2GRAY);elsegray = imgSrc.clone();gray.convertTo(gray, CV_64F);Mat xKernel = (Mat_(1, 3) -1, 0, 1);Mat yKernel = xKernel.t();Mat Ix, Iy;filter2D(gray, Ix, CV_64F, xKernel);filter2D(gray, Iy, CV_64F, yKernel);Mat Ix2, Iy2, Ixy;Ix2 = Ix.mul(Ix);Iy2 = Iy.mul(Iy);Ixy = Ix.mul(Iy);Mat gaussKernel = getGaussianKernel(7, 1);filter2D(Ix2, Ix2, CV_64F, gaussKernel);filter2D(Iy2, Iy2, CV_64F, gaussKernel);filter2D(Ixy, Ixy, CV_64F, gaussKernel);Mat cornerStrength(gray.size(), gray.type();for (int i = 0; i gray.rows; i+)for (int j = 0; j gray.cols; j+)double det_m = Ix2.at(i, j) * Iy2.at(i, j) - Ixy.at(i, j) * Ixy.at(i, j);double trace_m = Ix2.at(i, j) + Iy2.at(i, j);cornerStrength.at(i, j) = det_m - alpha * trace_m *trace_m;/ thresholddouble maxStrength;minMaxLoc(cornerStrength, NULL, &maxStrength, NULL, NULL);Mat dilated;Mat localMax;dilate(cornerStrength, dilated, Mat();compare(cornerStrength, dilated, localMax, CMP_EQ);Mat cornerMap;double qualityLevel = 0.01;double thresh = qualityLevel * maxStrength;cornerMap = cornerStrength thresh;bitwise_and(cornerMap, localMax, cornerMap);imgDst = cornerMap.c