imtophat

imtophat(img: np.ndarray, ksize: int | tuple[int, int] = (3, 3), kstruct: str | int | MORPH = MORPH.RECT) -> np.ndarray

• Description: Top-hat operation: The original image minus the result of the opening operation. For multi-channel images, each channel is processed independently. This operation is useful for extracting brighter areas than the original image, such as bright spots or small structures, while removing or reducing large bright areas.

• Parameters

  • img (np.ndarray): The input image.
  • ksize (int | tuple[int, int]): The size of the structuring element. Default is (3, 3).
  • kstruct (str | int | MORPH): Structuring element shape. Accepts MORPH.CROSS/RECT/ELLIPSE, string "CROSS"/"RECT"/"ELLIPSE", or an OpenCV integer. Default is MORPH.RECT.

• Example

  import numpy as np
  from capybara.vision.morphology import imtophat
  
  img = np.array([[1, 1, 1, 0, 0],
                  [1, 1, 1, 0, 0],
                  [1, 1, 1, 0, 0],
                  [0, 0, 1, 1, 0],
                  [0, 0, 0, 1, 1],
                  [0, 0, 0, 1, 1]], dtype=np.uint8)
  
  tophat_img = imtophat(img, ksize=3, kstruct='RECT')
  
  # Kernel will be like this:
  # >>> np.array([[1, 1, 1],
  #               [1, 1, 1],
  #               [1, 1, 1]], dtype=np.uint8)
  
  # After tophat, the image will be like this:
  # >>> np.array([[0, 0, 0, 0, 0],
  #               [0, 0, 0, 0, 0],
  #               [0, 0, 0, 0, 0],
  #               [0, 0, 1, 1, 0],
  #               [0, 0, 0, 0, 0],
  #               [0, 0, 0, 0, 0]], dtype=np.uint8)