Python으로 배우는 이미지 처리
Rebeca Gonzalez
Data Engineer
이미지를 전경과 배경으로 분할
이미지를 흑백으로 만듭니다
각 픽셀을 다음으로 설정합니다:

가장 간단한 영상 분할 방법

반드시 그레이스케일 이미지에서만 수행

# Obtain the optimal threshold value thresh = 127# Apply thresholding to the image binary = image > thresh# Show the original and thresholded show_image(image, 'Original') show_image(binary, 'Thresholded')

# Obtain the optimal threshold value thresh = 127# Apply thresholding to the image inverted_binary = image <= thresh# Show the original and thresholded show_image(image, 'Original') show_image(inverted_binary, 'Inverted thresholded')

전역(히스토그램 기반): 균일한 배경에 적합
지역(적응형): 불균일한 조명에 적합

from skimage.filters import try_all_threshold# 모든 결과 이미지 얻기 fig, ax = try_all_threshold(image, verbose=False)# 결과 플롯 표시 show_plot(fig, ax)

# Import the otsu threshold function from skimage.filters import threshold_otsu# Obtain the optimal threshold value thresh = threshold_otsu(image)# Apply thresholding to the image binary_global = image > thresh
# Show the original and binarized image
show_image(image, 'Original')
show_image(binary_global, 'Global thresholding')

# Import the local threshold function from skimage.filters import threshold_local# Set the block size to 35 block_size = 35# Obtain the optimal local thresholding local_thresh = threshold_local(text_image, block_size, offset=10)# Apply local thresholding and obtain the binary image binary_local = text_image > local_thresh
# Show the original and binarized image
show_image(text_image, 'Original')
show_image(binary_local, 'Local thresholding')

Python으로 배우는 이미지 처리