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| 1 | +# Source: "https://www.ijcse.com/docs/IJCSE11-02-03-117.pdf" |
| 2 | + |
| 3 | +# Importing necessary libraries |
| 4 | +import matplotlib.pyplot as plt |
| 5 | +import numpy as np |
| 6 | +from PIL import Image |
| 7 | + |
| 8 | + |
| 9 | +def segment_image(image: np.ndarray, thresholds: list[int]) -> np.ndarray: |
| 10 | + """ |
| 11 | + Performs image segmentation based on intensity thresholds. |
| 12 | +
|
| 13 | + Args: |
| 14 | + image: Input grayscale image as a 2D array. |
| 15 | + thresholds: Intensity thresholds to define segments. |
| 16 | +
|
| 17 | + Returns: |
| 18 | + A labeled 2D array where each region corresponds to a threshold range. |
| 19 | +
|
| 20 | + Example: |
| 21 | + >>> img = np.array([[80, 120, 180], [40, 90, 150], [20, 60, 100]]) |
| 22 | + >>> segment_image(img, [50, 100, 150]) |
| 23 | + array([[1, 2, 3], |
| 24 | + [0, 1, 2], |
| 25 | + [0, 1, 1]], dtype=int32) |
| 26 | + """ |
| 27 | + # Initialize segmented array with zeros |
| 28 | + segmented = np.zeros_like(image, dtype=np.int32) |
| 29 | + |
| 30 | + # Assign labels based on thresholds |
| 31 | + for i, threshold in enumerate(thresholds): |
| 32 | + segmented[image > threshold] = i + 1 |
| 33 | + |
| 34 | + return segmented |
| 35 | + |
| 36 | + |
| 37 | +if __name__ == "__main__": |
| 38 | + # Load the image |
| 39 | + image_path = "path_to_image" # Replace with your image path |
| 40 | + original_image = Image.open(image_path).convert("L") |
| 41 | + image_array = np.array(original_image) |
| 42 | + |
| 43 | + # Define thresholds |
| 44 | + thresholds = [50, 100, 150, 200] |
| 45 | + |
| 46 | + # Perform segmentation |
| 47 | + segmented_image = segment_image(image_array, thresholds) |
| 48 | + |
| 49 | + # Display the results |
| 50 | + plt.figure(figsize=(10, 5)) |
| 51 | + |
| 52 | + plt.subplot(1, 2, 1) |
| 53 | + plt.title("Original Image") |
| 54 | + plt.imshow(image_array, cmap="gray") |
| 55 | + plt.axis("off") |
| 56 | + |
| 57 | + plt.subplot(1, 2, 2) |
| 58 | + plt.title("Segmented Image") |
| 59 | + plt.imshow(segmented_image, cmap="tab20") |
| 60 | + plt.axis("off") |
| 61 | + |
| 62 | + plt.show() |
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