OpenCV Processing - Edge detection and Cropping

Question

How do i remove the irregular white pixels from the preprocessed image.

i have tried doing erosion and that would make all pixels black.

After Preprocessing:

Requirement:

My Code:

Mat  img, edges, erode, blurred, element;
element = getStructuringElement(cv::MORPH_RECT, cv::Size(7, 7), cv::Point(-1,-1) ); 

img = imread("img1925.jpeg");    //  read the image
cv::Canny(img, edges, 30, 255, 3);    // detect the edges with threshold limit

//    cv::erode(edges, erode, element);

GaussianBlur(edges, blurred, cv::Size(7, 7), 0);    // blurring

//    Rect ROI = boundingRect(blurred);       // draw rect for ROI
//    Mat src = thresh(ROI);

namedWindow("image", WINDOW_NORMAL);
imshow("image", blurred);
waitKey(0);
return 0;

Looking for suggestions!

Answer 1

I'm not sure what you mean by removing the irregular white pixels from the preprocessed image but if your goal is to extract a ROI of the object then here's an approach:

• Convert image to grayscale and Gaussian blur to smooth image
• Adaptive threshold to obtain a binary image
• Find contours and filter using contour area
• Extract the largest contour in the image and crop the ROI

---

Here's the result

If you cropped the ROI on the thresholded image, here's the result

I implemented it in Python but you can follow the same steps in C++

import cv2

image = cv2.imread('1.jpg')
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blur = cv2.GaussianBlur(gray, (7,7), 0)
thresh = cv2.adaptiveThreshold(blur,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY_INV,11,3)

cnts = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
cnts = sorted(cnts, key=cv2.contourArea, reverse=True)
for c in cnts:
    x,y,w,h = cv2.boundingRect(c)
    ROI = image[y:y+h, x:x+w]
    break

cv2.imwrite('ROI.png', ROI)
cv2.waitKey()