import cv2
o=cv2.imread('C:/Users/xpp/Desktop/Finger.png')#原始图像
cv2.imshow("original",o)
gray=cv2.cvtColor(o,cv2.COLOR_BGR2GRAY)#将彩色图片转换为灰度图
ret,thresh=cv2.threshold(gray,235,255,cv2.THRESH_BINARY)#将灰度图片转换为二值图片
contours,hierarchy=cv2.findContours(thresh,2,1)#计算图像轮廓
for cnt in contours:
hull=cv2.convexHull(cnt)#计算凸包
length=len(hull)
if length>5:
for i in range(length):
cv2.line(gray,tuple(hull[i][0]),tuple(hull[(i+1)%length][0]),(0,0,255),2)#绘制凸包
distA=cv2.pointPolygonTest(hull,(300,150),True)#点A到轮廓的距离
font=cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(gray,'A',(300,100),font,1,(0,255,0),3)
print("distA=",distA)
distB=cv2.pointPolygonTest(hull,(300,250),True)#点B到轮廓的距离
font=cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(gray,'B',(300,200),font,1,(0,255,0),3)
print("distB=",distB)
distC=cv2.pointPolygonTest(hull,(300,250),True)#点C到轮廓的距离
font=cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(gray,'C',(300,300),font,1,(0,255,0),3)
print("distC=",distC)
cv2.imshow("result1",gray)
cv2.waitKey()
cv2.destroyAllWindows()
distA= -44.67523126587924 distB= -35.353421065507135 distC= -35.353421065507135
算法:轮廓测量的是点到多边形(轮廓)的最短距离(垂线距离),又称点和多边形的关系测试。
retval=cv2.pointPolygonTest(contour, pt, measureDist)
本文分享自 图像处理与模式识别研究所 微信公众号,前往查看
如有侵权,请联系 cloudcommunity@tencent.com 删除。
本文参与 腾讯云自媒体同步曝光计划 ,欢迎热爱写作的你一起参与!