如何计算给定颜色图像中的角点

Question

I hope you are doing well. I want to count the corner points in the image of a given color. Like blue colour has two shapes how can i find and count that corner points

I have used the following code But It find out the corner of shape not color

import cv2
import numpy as np
import matplotlib.pyplot as plt

def cornerpoint(img):
    img = cv2.imread(img)
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    gray = np.float32(gray)
    dst = cv2.cornerHarris(gray,5,3,0.04)
    ret, dst = cv2.threshold(dst,0.1*dst.max(),255,0)
    dst = np.uint8(dst)
    ret, labels, stats, centroids = cv2.connectedComponentsWithStats(dst)
    criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 100, 0.001)
    corners = cv2.cornerSubPix(gray,np.float32(centroids),(5,5),(-1,-1),criteria)
    for i in range(1, len(corners)):
        print(corners[i])
    img[dst>0.1*dst.max()]=[0,0,0]
    plt.imshow(img)

cornerpoint('/content/shapes.png')

How can I proceed to count the corner points in the image of a given color?

Answer 1

In response to questions raised in the comments, here is one way to get the list of unique colors ignoring the anti-aliasing of the colors.

(You could also use morphology to thin your colored lines to remove the anti-aliased pixels)

• Read the input
• Reshape to 1D image of 3 channels
• Use np.unique to get the colors and counts
• Zip the colors and counts
• Put the zip into a list
• Sort the zipped list on count in reverse order
• Print only those colors that have counts above some threshold.
• (Note: other filters could be used to check colors against each other to be sure not too close or to remove colors near the background color. Etc)

Input:

import cv2
import numpy as np

# read image
img = cv2.imread('colored_polygons.png')

# reshape img to 1 column of 3 colors
# -1 means figure out how big it needs to be for that dimension
img2 = img.reshape(-1,3)

# get the unique colors
colors, counts = np.unique(img2, return_counts=True, axis=0)

# zip colors, counts
unique = zip(colors,counts)

# make list of color, count
cc_list = []
for color, count in unique:
    cc_list.append((color, count))
    
# function to define key as second element (count)
def takeSecond(elem):
    return elem[1]

# sort cc_list on counts
cc_list.sort(key=takeSecond, reverse=True)

# print sorted list and threshold on count
index = 0
for item in cc_list:
    color = item[0]
    count = item[1]
    if count > 5000:
        index += 1
        print("index:", index, "count:", count, "color:", color)

List of Top Unique Colors:

index: 1 count: 428771 color: [255 255 255]
index: 2 count: 15735 color: [0 0 0]
index: 3 count: 9760 color: [ 14 127   0]
index: 4 count: 9160 color: [255  38   0]
index: 5 count: 8893 color: [  0   0 255]