輪郭の検出

Pythonで学ぶ画像処理

Rebeca Gonzalez

Data Engineer

輪郭の検出

大きさを測る
形状を分類
物体数を数える

ドミノの点の合計: 29。

二値画像

二値画像は、しきい値処理またはエッジ検出で作成できます。

scikit-image で輪郭を検出

画像の準備

画像を2Dグレースケールに変換します。

# Make the image grayscale
image = color.rgb2gray(image)

scikit-image で輪郭を検出

画像の準備

画像を二値化します。

# Obtain the thresh value
thresh = threshold_otsu(image)

# Apply thresholding
thresholded_image = image > thresh

scikit-image で輪郭を検出

次に find_contours() を使います。

# Import the measure module
from skimage import measure

# Find contours at a constant value of 0.8
contours = measure.find_contours(thresholded_image, 0.8)

一定レベル値

輪郭検出の手順

from skimage import measure
from skimage.filters import threshold_otsu

# Make the image grayscale
image = color.rgb2gray(image)

# Obtain the optimal thresh value of the image
thresh = threshold_otsu(image)

# Apply thresholding and obtain binary image
thresholded_image = image > thresh


# Find contours at a constant value of 0.8
contours = measure.find_contours(thresholded_image, 0.8)

輪郭検出の手順

結果

輪郭の配列形状

Contours: (n,2) 形状のndarrayのリスト。

for contour in contours:
    print(contour.shape)

(433, 2)
(433, 2)
(401, 2)
(401, 2) 
(123, 2)
(123, 2) 
(59, 2)
(59, 2)
(59, 2)
(57, 2)
(57, 2)
(59, 2)
(59, 2)

輪郭の配列形状

for contour in contours:
    print(contour.shape)

(433, 2)
(433, 2) --> Outer border
(401, 2)
(401, 2)
(123, 2)
(123, 2)
(59, 2)
(59, 2)
(59, 2)
(57, 2)
(57, 2)
(59, 2)
(59, 2)

輪郭の配列形状

for contour in contours:
    print(contour.shape)

(433, 2)
(433, 2) --> Outer border
(401, 2)
(401, 2) --> Inner border
(123, 2)
(123, 2) 
(59, 2)
(59, 2)
(59, 2)
(57, 2)
(57, 2)
(59, 2)
(59, 2)

輪郭の配列形状

for contour in contours:
    print(contour.shape)

(433, 2)
(433, 2) --> Outer border
(401, 2)
(401, 2) --> Inner border
(123, 2)
(123, 2) --> Divisory line of tokens
(59, 2)
(59, 2)
(59, 2)
(57, 2)
(57, 2)
(59, 2)
(59, 2)

輪郭の配列形状

for contour in contours:
    print(contour.shape)

(433, 2)
(433, 2) --> Outer border
(401, 2)
(401, 2) --> Inner border
(123, 2)
(123, 2) --> Divisory line of tokens
(59, 2)
(59, 2)
(59, 2)
(57, 2)
(57, 2)
(59, 2)
(59, 2) --> Dots

点の数: 7。

Passons à la pratique !

Pythonで学ぶ画像処理