How to get the accurate percentage of infected region?

Question

I'm creating a preprocessing in opencv python that computes the total area, infected region and percentage of region interest.

import cv2
import numpy as np           
import argparse

img1 = cv2.imread('19.jpg')
img = cv2.resize(img1, (0,0), fx=0.5, fy=0.5)
original = img.copy()
neworiginal = img.copy()

blur1 = cv2.GaussianBlur(img,(3,3),1)

newimg = np.zeros((img.shape[0], img.shape[1],3),np.uint8)
criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER , 10 ,1.0)
img = cv2.pyrMeanShiftFiltering(blur1, 20, 30, newimg, 0, criteria)

blur = cv2.GaussianBlur(img,(11,11),1)

kernel = np.ones((5,5),np.uint8)
canny = cv2.Canny(blur, 200, 290)
res = cv2.morphologyEx(canny,cv2.MORPH_CLOSE, kernel)
canny = cv2.cvtColor(canny,cv2.COLOR_GRAY2BGR)
cv2.imshow('Canny',res)

hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
lower = np.array([5,25,25])
upper = np.array([70,255,255])

mask = cv2.inRange(hsv, lower, upper)

res = cv2.bitwise_and(hsv,hsv, mask= mask)
gray = cv2.cvtColor(res,cv2.COLOR_BGR2GRAY)
ret, thresh = cv2.threshold(gray,0,255,cv2.THRESH_BINARY+cv2.THRESH_OTSU)
_, contours, hierarchy = cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_NONE)


for i in contours:
    cnt = cv2.contourArea(i)
    #M = cv2.momens(i)
    #cx = int(M['m10']/M['m00'])
    if cnt > 1000:  
        cv2.drawContours(img, [i], 0, (0,0,255), 2)

gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
ret, thresh = cv2.threshold(gray,0,255,cv2.THRESH_BINARY+cv2.THRESH_OTSU)
_, contours, hierarchy = cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_NONE)
cnt = max(contours, key=cv2.contourArea)
Tarea = cv2.contourArea(cnt)
cv2.imshow('img', img)

height, width, _ = canny.shape
min_x, min_y = width, height
max_x = max_y = 0
frame = canny.copy()

for contour, hier in zip(contours, hierarchy):

 (x,y,w,h) = cv2.boundingRect(contour)
            min_x, max_x = min(x, min_x), max(x+w, max_x)
            min_y, max_y = min(y, min_y), max(y+h, max_y)
            if w > 80 and h > 80:
                cv2.rectangle(frame, (x,y), (x+w,y+h), (255, 0, 0), 2)
                roi = img[y:y+h , x:x+w]
                originalroi = original[y:y+h , x:x+w]
if max_x - min_x > 0 and max_y - min_y > 0:
    cv2.rectangle(frame, (min_x, min_y), (max_x, max_y), (255, 0, 0), 2)

img = roi

imghls = cv2.cvtColor(roi, cv2.COLOR_BGR2HSV)

imghls[np.where((imghls==[30,200,2]).all(axis=2))] = [0,200,0]

huehls = imghls[:,:,0]

huehls[np.where(huehls==[0])] = [35]

#Thresholding on hue image
ret, thresh = cv2.threshold(huehls,28,255,cv2.THRESH_BINARY_INV)
cv2.imshow('thresh', thresh)


mask = cv2.bitwise_and(originalroi,originalroi,mask = thresh)

_, contours,heirarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)

Infarea = 0

for x in range(len(contours)):

    cv2.drawContours(originalroi,contours[x],-1,(0,0,255),2)

    cv2.imshow('Contour masked',originalroi)

    #Calculating area of infected region
    Infarea += cv2.contourArea(contours[x])




#if Infarea > Tarea:
    #Tarea = img.shape[0]*img.shape[1]

print ('_______________________\n| Total area: ' + str(Tarea) + '   |\n|_____________________|')

#Finding the percentage of infection in the banana
print ('\n__________________________\n| Infected area: ' + str(Infarea) + ' |\n|________________________|')

try:
    per = 100 * Infarea/Tarea

except ZeroDivisionError:
    per = 0

print( '\n_________________________________________________\n| Percentage of infection region: ' + str(per) + ' |\n|_______________________________________________|')


cv2.imshow('orig',original)

enter image description here

Here's the image I've used in this particular code my problem is in getting the region of interest its not accurate result if we see in our own vision the infected area must be in 50% I think. Any idea how to get the best accuracy percentage of region interest because the result is not accurate as well.

Yes because if we see in our vision the result in this code is not exactly. If we look at the infected area it must be less or up to 50% but the result of infected area is super low, is there any idea to get the accurate result of infected area? — TrialAndError, Feb 11 '20 at 04:40
Why the [duplicate](https://stackoverflow.com/questions/60160903)? — HansHirse, Feb 11 '20 at 05:04

score 0 · Answer 1 · answered Feb 11 '20 at 05:41

If your back ground will not be in the same color with the infected region, you can simply use color difference. I used C++ but can be converted to Python easily. Here is my approach:

#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "highgui.h"
#include <stdlib.h>
#include <stdio.h>
#include <iostream>

using namespace cv;
using namespace std;

int main( int argc, char** argv )
{
    Mat src = imread( "/ur/image/directory/banana.jpg",CV_LOAD_IMAGE_GRAYSCALE );

    imshow( "Source", src );

    //check all pixels and change pixel values according to refrences
    for(int i=0; i<src.rows; i++)
    {
        for(int j=0;j<src.cols;j++)
        {
            if(src.at<uchar>(Point(j,i))>200)
                src.at<uchar>(Point(j,i)) = 0;
            else if(src.at<uchar>(Point(j,i))<30)
                src.at<uchar>(Point(j,i)) = 255;
            else
                src.at<uchar>(Point(j,i)) = 125;
        }
    }

    imshow( "First Process", src );

    Mat filtered_img;
    medianBlur ( src, filtered_img, 5 );

    imshow( "After Median", filtered_img );


    double deformation_counter = 0;
    double clean_counter = 0;

    //check all pixels and count them
    for(int i=0; i<src.rows; i++)
    {
        for(int j=0;j<src.cols;j++)
        {
            if(src.at<uchar>(Point(j,i))==255)
                deformation_counter++;
            if(src.at<uchar>(Point(j,i))==125)
                clean_counter++;
        }
    }

    double percentage = deformation_counter/(deformation_counter+clean_counter);

    cout<<percentage<<endl;

    waitKey(0);
    return 0;
}

Source image:

First change:

Result:

My calculated percentage is 0.28(%28). Back ground is eliminated by making black — Yunus Temurlenk, Feb 11 '20 at 05:42
so i need to change my background for getting the region interest to get the higher result? — TrialAndError, Feb 11 '20 at 05:43
No, I changed it with the code. Just your back ground color shouldnt be same with bananas and black. — Yunus Temurlenk, Feb 11 '20 at 05:44
can you help to convert in python, im gonna used that for my reference, I don't know how to use c++. — TrialAndError, Feb 11 '20 at 05:45
Check [this link](https://stackoverflow.com/questions/28981417/how-do-i-access-the-pixels-of-an-image-using-opencv-python) and see how to read every pixel and change them. I just changed pixels and used median blur. Thats all not complicated. — Yunus Temurlenk, Feb 11 '20 at 05:47

How to get the accurate percentage of infected region?

1 Answers1