【发布时间】:2020-12-22 15:10:46
【问题描述】:
我在我的二进制图像上使用了Projection Profile 方法来获取纠偏版本。一切都很好,但旋转后的图像有黑色区域,其中应用了偏斜。 如何将该区域转换为白色而不是黑色。下面是投影配置文件的代码。
def correct_skew(image, delta=1, limit=5):
"""
image : input
delta : sampling in the -limit,limit + delta range
limit : range of angles to explore
"""
# Function that returns the score of histogram for the given angle at which we check
def determine_score(arr, angle):
"""
arr : binarized image
angle : angle at which we calcuate the score
"""
data = inter.rotate(arr, angle, reshape=False, order=0)
histogram = np.sum(data, axis=1)
score = np.sum((histogram[1:] - histogram[:-1]) ** 2)
return histogram, score
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]
scores = []
angles = np.arange(-limit, limit + delta, delta)
for angle in angles:
histogram, score = determine_score(thresh, angle)
scores.append(score)
best_angle = angles[scores.index(max(scores))]
(h, w) = image.shape[:2]
center = (w // 2, h // 2)
M = cv2.getRotationMatrix2D(center, best_angle, 1.0)
rotated = cv2.warpAffine(image, M, (w, h), flags=cv2.INTER_CUBIC)
return best_angle, rotated
这是校正后的图像:
【问题讨论】:
标签: opencv image-processing python-imaging-library scikit-image opencv-python