Segment image and highlight object border using python

Question

I’m testing some algorithms to improve the image quality that my hardware is getting. I have in the image a pick and I would like to highlight the object contained in it.

I used the code below to equalize the image, but I was not successful.

import cv2
import numpy as np

def histogram_equalize(img):
b, g, r = cv2.split(img)
red = cv2.equalizeHist(r)
green = cv2.equalizeHist(g)
blue = cv2.equalizeHist(b)
return cv2.merge((blue, green, red))
img = cv2.imread('pos20.jpg')

img_yuv = cv2.cvtColor(img, cv2.COLOR_BGR2YUV)

# equalize the histogram of the Y channel
img_yuv[:,:,0] = cv2.equalizeHist(img_yuv[:,:,0])

# convert the YUV image back to RGB format
img_output = cv2.cvtColor(img_yuv, cv2.COLOR_YUV2BGR)

cv2.imshow('Color input image', img)
cv2.imshow('Histogram equalized', img_output)
cv2.imwrite('20.jpg',img_output)

cv2.waitKey(0)

Output:

what is the best algorithm to improve image quality and highlight the edge of the object?

Answer 1

Really this image "is bone", and your question even more, :-), but maybe applying something more related to segmentation, you can have better results.

import cv2
import numpy as np
from matplotlib import pyplot as plt
img = cv2.imread('img1.jpg',0)
ret,thresh1 = cv2.threshold(img,127,255,cv2.THRESH_BINARY)
ret,thresh2 = cv2.threshold(img,127,255,cv2.THRESH_BINARY_INV)
ret,thresh3 = cv2.threshold(img,127,255,cv2.THRESH_TRUNC)
ret,thresh4 = cv2.threshold(img,127,255,cv2.THRESH_TOZERO)
ret,thresh5 = cv2.threshold(img,127,255,cv2.THRESH_TOZERO_INV)
titles = ['Original Image','BINARY','BINARY_INV','TRUNC','TOZERO','TOZERO_INV']
images = [img, thresh1, thresh2, thresh3, thresh4, thresh5]
for i in xrange(6):
    plt.subplot(2,3,i+1),plt.imshow(images[i],'gray')
    plt.title(titles[i])
    plt.xticks([]),plt.yticks([])
plt.show()