在 OpenCV（或 skimage）中使用 Projection Profile Deskew 方法后，将旋转图像的背景更改为白色而不是黑色

Question

我在我的二进制图像上使用了 Projection Profile 方法来获得去歪斜版本。一切都很好，但旋转后的图像有黑色区域，其中应用了歪斜校正。 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：

原始二进制图像：

Answer 1

cv2.warpaffine 文档指出该函数采用可选参数，即 borderValue。默认情况下，此值为 (0, 0, 0)，您可以通过调用 warpaffine 例程来更改此值：

rotated = cv2.warpAffine(image, M, (w, h), flags=cv2.INTER_CUBIC, borderMode = cv2.BORDER_CONSTANT, borderValue=np.array([255, 255, 255]))

在 OpenCV（或 skimage）中使用 Projection Profile Deskew 方法后，将旋转图像的背景更改为白色而不是黑色

Change the background of rotated image to White instead of black after using Projection Profile Deskew method in OpenCV (or skimage)

opencv

image-processing

python-imaging-library

scikit-image

opencv-python