OpenCV Detect scratches on fruits

Question

For a little experiment in Python I'm doing I want to find small scratches on fruits. The scratches are very small and hard to detect by human eye.

I'm using a high resolution camera for that experiment.

Here is the defect I want to detect:

Original Image:

This is my result with very few lines of code:

So I found the contours of my fruit. How can I proceed to finding the scratch? The RGB Value is similar to other parts of the fruit. So how can I differentiate between A scratch, and a part of the fruit?

My code:

# Imports
import numpy as np
import cv2
import time

# Read Image & Convert
img = cv2.imread('IMG_0441.jpg')
result = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)

# Filtering
lower = np.array([1,60,50])
upper = np.array([255,255,255])
result = cv2.inRange(result, lower, upper)
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(9,9))
result = cv2.dilate(result,kernel)

# Contours
im2, contours, hierarchy = cv2.findContours(result.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
result = cv2.cvtColor(result, cv2.COLOR_GRAY2BGR)
if len(contours) != 0:
    for (i, c) in enumerate(contours):
        area = cv2.contourArea(c)
        if area > 100000:
            print(area)
            cv2.drawContours(img, c, -1, (255,255,0), 12)
            x,y,w,h = cv2.boundingRect(c)            
            cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),12)

# Stack results
result = np.vstack((result, img))
resultOrig = result.copy()

# Save image to file before resizing
cv2.imwrite(str(time.time())+'_0_result.jpg',resultOrig)

# Resize
max_dimension = float(max(result.shape))
scale = 900/max_dimension
result = cv2.resize(result, None, fx=scale, fy=scale)

# Show results
cv2.imshow('res',result)

cv2.waitKey(0)
cv2.destroyAllWindows()

Answer 1

I changed your image to HSL colour space. I can't see the scratch in the L channel, so the greyscale approach suggested earlier is going to be difficult. But the scratch is quite noticeable in the hue plane.

You could use an edge detector to find the blemish in the hue channel. Here I use a difference of gaussians detector (with sizes 20 and 4).