How to crop and save segmented objects from an image?

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I have a hyperspectral image. In each image, there are many objects. I have to segment, crop, and save them as separate images. The segmented image after applying the thresholding is as below:

enter image description here

The problem is that I have to crop the segmented objects and save them. How it can be done?

image-segmentation computer-vision image-processing image python
1 Answers

Here's a simple approach:

  1. Obtain binary image. Load the image, convert to grayscale, and Otsu's threshold to obtain a binary image.

  2. Remove noise. We morphological operations to remove any particles of noise in the image.

  3. Extract objects. From here we find contours, obtain each bounding rectangle then extract and save each ROI using Numpy slicing.

Detected objects

enter image description here

Saved ROIs

enter image description here

import cv2
import numpy as np

# Load image, grayscale, Otsu's threshold
image = cv2.imread('1.jpg')
original = image.copy()
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]

# Morph open to remove noise
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5,5))
opening = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel, iterations=1)

# Find contours, obtain bounding box, extract and save ROI
ROI_number = 0
cnts = cv2.findContours(opening, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
for c in cnts:
    x,y,w,h = cv2.boundingRect(c)
    cv2.rectangle(image, (x, y), (x + w, y + h), (36,255,12), 2)
    ROI = original[y:y+h, x:x+w]
    cv2.imwrite('ROI_{}.png'.format(ROI_number), ROI)
    ROI_number += 1

cv2.imshow('image', image)
cv2.imshow('thresh', thresh)
cv2.imshow('opening', opening)
cv2.waitKey()
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