使用OpenCV自动进行红色阈值化

Question

Heres my input image:

I am plotting histogram of this image using the following code:

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

img = cv2.imread('red.jpg')
color = ('b','g','r')
for i,col in enumerate(color):
    histr = cv2.calcHist([img],[i],None,[256],[0,256])
    plt.plot(histr,color = col)
    plt.xlim([0,256])
plt.show()

Here is the plotted histogram output: On the left hand side is the original histogram and on the right hand side is the zoomed version:

My starting point is 255 and ending point is zero.

All my important data lies on the range of 235 to 255. As at 235 the line becomes straight (pl. see right hand side of histogram)

I want to write a python - opencv code which finds out when red line of histogram becomes straight and once the number is found after which the line shows minimum deviation delete all the remaining pixels from the image. In above case delete pixels having value (0 to 235). How can this be achieved ?

Answer 1

Histogram is basically arrays (bins). The opencv histogram bins you create, you can check for the number of values & mean values in each bin, and compare it with previous bin. (More like a sliding window). If you find the difference to be greater than a threshold, then consider them to be chosen bins(pixels).

This is a technique used to identify peaks in a 1D array.