OpenCV图像处理（八）-优快云博客

本文链接：https://blog.youkuaiyun.com/qwertawwar/article/details/118356537

本文介绍了使用OpenCV进行轮廓分析的技术，包括凸包绘制、凸缺陷检测和轮廓特征提取等关键步骤。通过实例展示了如何利用Python实现这些技术，并对轮廓的宽高比、极点等属性进行了探讨。

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一.凸包绘制

import cv2
img = cv2.imread('contours2.png',1)
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

ret,binary = cv2.threshold(gray,127,255,cv2.EHRESH_BINARY)

contours,hierarchy = cv2.findContours(binary,cv2.RETE_LIST,cv2.CHAIN_APPROX_NONE)
cnt = contours[0]

hull = cv2.convexHull(cnt)
cv2.polylines(img,[hull],True,(255,0,0),2)
cv2.imshow('line',img)
cv2.waitKey()
CV2.drstroyAllWindows()

二.凸缺陷检测

import cv2
0=cv2.imread('contours2.png')
gray = cv2.cvtColor(0,cv2.COLOR_BGR2GRAY)
ret,binary = cv2.threshold(gray,127,255,cv2.THRESH_BINARY)
contours,hierarchy = cv2.findContours(binary,cv2.RETE_TREE,cv2.CHAIN_APPROX_SIMPLE)

cnt = contours[0]
hull = cv2.convexHull(cnt,returnPoints = False)
defects = cv2.converxityDefects(cnt,hull)

for i in range(defects.shape[0]):
    s,e,f,d = defects[i,0]
    start = tuple(cnt[s][0])
    end = tuple(cnt[e][0])
    far = tuple(cnt[f][0])
    cv2.line(o,start,end,[0,0,255],2)
    cv2.circle(0,far,5,[255,0,0],-1)

cv2.imshow('result',0)
cv2.waitKey(0)
cv2.destroyAllWindows()

三.轮廓常见特征

宽高比