Function segment_image

computer_vision/intensity_based_segmentation.py:9–34

Performs image segmentation based on intensity thresholds. Args: image: Input grayscale image as a 2D array. thresholds: Intensity thresholds to define segments. Returns: A labeled 2D array where each region corresponds to a threshold range. Exam

(image: np.ndarray, thresholds: list[int])

def segment_image(image: np.ndarray, thresholds: list[int]) -> np.ndarray:
    """
    Performs image segmentation based on intensity thresholds.

    Args:
        image: Input grayscale image as a 2D array.
        thresholds: Intensity thresholds to define segments.

    Returns:
        A labeled 2D array where each region corresponds to a threshold range.

    Example:
        >>> img = np.array([[80, 120, 180], [40, 90, 150], [20, 60, 100]])
        >>> segment_image(img, [50, 100, 150])
        array([[1, 2, 3],
               [0, 1, 2],
               [0, 1, 1]], dtype=int32)
    """
    # Initialize segmented array with zeros
    segmented = np.zeros_like(image, dtype=np.int32)

    # Assign labels based on thresholds
    for i, threshold in enumerate(thresholds):
        segmented[image > threshold] = i + 1

    return segmented


if __name__ == "__main__":