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Date: Thu, 9 Dec 2021 15:30:22 +0800
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+# 寻找图像的轮廓
+
+轮廓是由连续的点组成的曲线。轮廓与边缘很相似，但轮廓是连续的，边缘不一定都连续。
+
+轮廓反映了物体的基本外形，常用于形状分析和物体的检测和识别。
+
+OpenCV 提供函数 **cv.findContours()** 对二值图像寻找轮廓，函数 **cv2.drawContours()** 绘制轮廓。
+
+**函数说明：**
+
+```
+cv.boxFilter(src, ddepth, ksize[, dst[, anchor[, normalize[, borderType]]]]) → dst
+```
+
+我们从康熙御笔书法中提取轮廓，据说这是一种经典的书画复制技法。下图从上到下分别是：
+* 康熙御笔原图
+* 康熙御笔碑帖图
+* 康熙御笔轮廓图
+
+![](./ContoursOutput.jpg)
+
+下面对康熙御笔寻找轮廓实现代码正确的是？
+
+##  答案
+
+```
+import cv2 as cv
+
+if __name__ == '__main__':
+    img = cv.imread("Contours.jpg", flags=1)
+    imgGray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
+
+    ret, thresh = cv.threshold(imgGray, 127, 255, cv.THRESH_BINARY_INV)
+    image, contours, hierarchy = cv.findContours(thresh, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
+    contourPic = cv.drawContours(img, contours, -1, (0, 0, 255), 2)
+
+    cv.imshow("ContourPicture", contourPic)
+    cv.waitKey(0)
+```
+
+##  选项
+
+###  使用了灰度图而不是二值图来查找轮廓
+
+```
+import cv2 as cv
+
+if __name__ == '__main__':
+    img = cv.imread("Contours.jpg", flags=1)
+    imgGray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
+
+    ret, thresh = cv.threshold(imgGray, 127, 255, cv.THRESH_BINARY_INV)
+    image, contours, hierarchy = cv.findContours(imgGray, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
+    contourPic = cv.drawContours(img, contours, -1, (0, 0, 255), 2)
+
+    cv.imshow("ContourPicture", contourPic)
+    cv.waitKey(0)
+```
+
+###  阈值处理时的阈值设置过大
+
+```
+import cv2 as cv
+
+if __name__ == '__main__':
+    img = cv.imread("Contours.jpg", flags=1)
+    imgGray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
+
+    ret, thresh = cv.threshold(imgGray, 205, 255, cv.THRESH_BINARY_INV)
+    image, contours, hierarchy = cv.findContours(thresh, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
+    contourPic = cv.drawContours(img, contours, -1, (0, 0, 255), 2)
+
+    cv.imshow("ContourPicture", contourPic)
+    cv.waitKey(0)
+```
+
+###  函数 findContours 缺少输出参数 image
+
+```
+import cv2 as cv
+
+if __name__ == '__main__':
+    img = cv.imread("Contours.jpg", flags=1)
+    imgGray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
+
+    ret, thresh = cv.threshold(imgGray, 127, 255, cv.THRESH_BINARY_INV)
+    contours, hierarchy = cv.findContours(thresh, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
+    contourPic = cv.drawContours(img, contours, -1, (0, 0, 255), 2)
+
+    cv.imshow("ContourPicture", contourPic)
+    cv.waitKey(0)
+```
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