史上最简单&最全&最基础&入门到精通的opencv图像处理 第十九课：图像近似

一、代码部分

代码如下（示例）：

#图像近似
import cv2 #opencv BGR
import matplotlib.pyplot as plt #包导入
import numpy as np

def cv_show(img,name):
    cv2.imshow(name,img)
    cv2.waitKey()
    cv2.destroyAllWindows()

img = cv2.imread('C:/Users/akaak/Pictures/OpenCV/contours2.png')

gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
ret, thresh = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY)
contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
cnt = contours[0]

draw_img = img.copy()
res = cv2.drawContours(draw_img, [cnt], -1, (0, 0, 255), 2)#图像轮廓
cv_show(res,'res')

epsilon = 0.05*cv2.arcLength(cnt,True)#周长的0.15倍
approx = cv2.approxPolyDP(cnt,epsilon,True)#近似函数

draw_img = img.copy()
res = cv2.drawContours(draw_img, [approx], -1, (0, 0, 255), 2)#近似之后再进行图像轮廓提取
cv_show(res,'res')

img = cv2.imread('C:/Users/akaak/Pictures/OpenCV/contours.png')

gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
ret, thresh = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY)
contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
cnt = contours[0]

x,y,w,h = cv2.boundingRect(cnt)
img = cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),2)
cv_show(img,'img')

area = cv2.contourArea(cnt)
x, y, w, h = cv2.boundingRect(cnt)
rect_area = w * h
extent = float(area) / rect_area
print ('轮廓面积与边界矩形比',extent)

(x,y),radius = cv2.minEnclosingCircle(cnt)
center = (int(x),int(y))
radius = int(radius)
img = cv2.circle(img,center,radius,(0,255,0),2)
cv_show(img,'img')

二、运行结果

总结

完成图像的近似