Approximating Contours and Convex Hull

cv2.approxPolyDP(contour, Approximation Accuracy, Closed)

contour – is the individual contour we wish to approximate
Approximation Accuracy – Important parameter is determining the accuracy of the approximation. Small values give precise- approximations, large values give more generic approximation. A good rule of thumb is less than 5% of the contour perimeter
Closed – a Boolean value that states whether the approximate contour should be open or closed



In [5]:

    
import numpy as np
import cv2

# Load image and keep a copy
image = cv2.imread('images/house.jpg')
orig_image = image.copy()
cv2.imshow('Original Image', orig_image)
cv2.waitKey(0) 

# Grayscale and binarize
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
ret, thresh = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY_INV)

# Find contours 
contours, hierarchy = cv2.findContours(thresh.copy(), cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE)

# Iterate through each contour and compute the bounding rectangle
for c in contours:
    x,y,w,h = cv2.boundingRect(c)
    cv2.rectangle(orig_image,(x,y),(x+w,y+h),(0,0,255),2)    
    cv2.imshow('Bounding Rectangle', orig_image)

cv2.waitKey(0) 
    
# Iterate through each contour and compute the approx contour
for c in contours:
    # Calculate accuracy as a percent of the contour perimeter
    accuracy = 0.03 * cv2.arcLength(c, True)
    approx = cv2.approxPolyDP(c, accuracy, True)
    cv2.drawContours(image, [approx], 0, (0, 255, 0), 2)
    cv2.imshow('Approx Poly DP', image)
    
cv2.waitKey(0)   
cv2.destroyAllWindows()

Convex Hull



In [8]:

    
import numpy as np
import cv2

image = cv2.imread('images/hand.jpg')
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

cv2.imshow('Original Image', image)
cv2.waitKey(0) 

# Threshold the image
ret, thresh = cv2.threshold(gray, 176, 255, 0)

# Find contours 
contours, hierarchy = cv2.findContours(thresh.copy(), cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE)
    
# Sort Contors by area and then remove the largest frame contour
n = len(contours) - 1
contours = sorted(contours, key=cv2.contourArea, reverse=False)[:n]

# Iterate through contours and draw the convex hull
for c in contours:
    hull = cv2.convexHull(c)
    cv2.drawContours(image, [hull], 0, (0, 255, 0), 2)
    cv2.imshow('Convex Hull', image)

cv2.waitKey(0)    
cv2.destroyAllWindows()



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