目标：
灰度化--->>>阈值化--->>>形态学：
因为玉米都连在一起了，没办法通过形态学分割，所以进行距离变换：
阈值操作，这点需要进行可变的阈值进行观察，找到一个合适的阈值：
轮廓查找计数：
遇到的问题：
A.
1.用下面这个自适应阈值必须进行数据的转换，不能直接传入数据！不然程序一直崩溃，找了很久才发现。
2.最后一个参数给个0就可以了，倒数第二个参数为大于1的数。
3.倒数第二个参数一定为基数，当为偶数的时候一直奔溃！！！
Middle_image.convertTo(show_image, CV_8U);
adaptiveThreshold(show_image, output_image, 255, ADAPTIVE_THRESH_GAUSSIAN_C, THRESH_BINARY, 79, 0);
B.
1.下面这个距离变换第三个参数：名义上是那么多参数，我试了一下可以使用的是前四个，后面使用之后就崩溃，具体原因我也不知道。
1 enum DistanceTypes { 2 DIST_USER = -1, //!< User defined distance 3 DIST_L1 = 1, //!< distance = |x1-x2| + |y1-y2| 4 DIST_L2 = 2, //!< the simple euclidean distance 5 DIST_C = 3, //!< distance = max(|x1-x2|,|y1-y2|) 6 DIST_L12 = 4, //!< L1-L2 metric: distance = 2(sqrt(1+x*x/2) - 1)) 7 DIST_FAIR = 5, //!< distance = c^2(|x|/c-log(1+|x|/c)), c = 1.3998 8 DIST_WELSCH = 6, //!< distance = c^2/2(1-exp(-(x/c)^2)), c = 2.9846 9 DIST_HUBER = 7 //!< distance = |x|<c ? x^2/2 : c(|x|-c/2), c=1.345 10 };
2.输出参数要求是8-bit or 32-bit floating-point，就是CV_8FU1、CV_32FU1，其实直接定义个Mat，然后传入数据就行了。
distanceTransform(Middle_image, Middle_image, DIST_L2, DIST_MASK_3, 5);
代码：
C.
定义数组长度的时候千万多比实际使用多一点，不然就一直崩溃！！！
char countText[50];//
sprintf(countText,"The Corn count is : %d", static_cast<int>(i));
1 #define _CRT_SECURE_NO_WARNINGS 2 #include<iostream> 3 #include <opencv2/opencv.hpp> 4 #include <math.h> 5 using namespace cv; 6 using namespace std; 7 8 RNG rng(12345); 9 10 Mat input_image, threshold_image, output_image, Middle_image, show_image; 11 int g_value = 68; 12 13 void AdjustThresholdValue(int, void*); 14 15 int main(int argc, char**argv) 16 { 17 input_image = imread("1.jpg"); 18 if (input_image.data == NULL) { 19 return -1; cout << "can't open image.../"; 20 } 21 imshow("Sourse Image", input_image); 22 cvtColor(input_image, Middle_image, COLOR_RGB2GRAY); 23 //imshow("Gray Image", Middle_image); 24 threshold(Middle_image, Middle_image,0,255, THRESH_BINARY| THRESH_TRIANGLE); 25 //imshow("Gray Image", Middle_image); 26 Mat kernel = getStructuringElement(MORPH_RECT, Size(5, 5), Point(-1, -1)); 27 morphologyEx(Middle_image, Middle_image, MORPH_CLOSE,kernel); 28 //imshow("morphology Image", Middle_image); 29 morphologyEx(Middle_image, Middle_image, MORPH_DILATE, kernel); 30 imshow("dilate Image", Middle_image); 31 bitwise_not(Middle_image, Middle_image); 32 imshow("distance Image", Middle_image); 33 distanceTransform(Middle_image, Middle_image, DIST_L2, DIST_MASK_3, 5); 34 normalize(Middle_image, Middle_image, 0, 1, NORM_MINMAX); 35 imshow("distance Image", Middle_image); 36 37 Middle_image.convertTo(show_image, CV_8U); 38 namedWindow("threshold Image",1); 39 createTrackbar("value","threshold Image",&g_value,100, AdjustThresholdValue); 40 AdjustThresholdValue(0,0); 41 waitKey(0); 42 return 0; 43 } 44 45 void AdjustThresholdValue(int, void*) 46 { 47 int k = (g_value * 2 + 1); 48 adaptiveThreshold(show_image, output_image, 255, ADAPTIVE_THRESH_GAUSSIAN_C, THRESH_BINARY, k, 0); 49 Mat kernel = getStructuringElement(MORPH_RECT, Size(9, 9), Point(-1, -1)); 50 morphologyEx(output_image, output_image, MORPH_OPEN, kernel); 51 imshow("threshold Image", output_image); 52 Mat temp; 53 output_image.copyTo(temp); 54 vector<vector<Point>> contours; 55 vector<Vec4i> hierarchy; 56 findContours(output_image,contours,hierarchy, RETR_TREE, CHAIN_APPROX_NONE,Point(-1,-1)); 57 size_t i; 58 for (i = 0; i < contours.size(); i++) 59 { 60 drawContours(output_image, contours, static_cast<int>(i), Scalar(255, 0, 0), 2); 61 } 62 char countText[50];//定义数组长度的时候千万多比实际使用多一点，不然就一直崩溃！！！ 63 sprintf(countText,"The Corn count is : %d", static_cast<int>(i)); 64 putText(output_image, countText, Point(30,30), FONT_HERSHEY_SIMPLEX, 1.0, Scalar(255, 255, 255), 2, 16); 65 imshow("Contours Image", output_image); 66 }
参考：贾老师opencv系列