python - 使用 OpenCV 和 Python 提取楼层布局和阈值

Question

我试过使用 SSIM提取两个图像之间的差异以仅获取地板面积(image_a 是原始图像，image_b 已绘制(paint)地板)。

预期的输出是阈值掩码。

我遇到的问题是 ssim 差异的阈值在我的情况下不起作用(示例如下所示)。

有人可以提供更好的阈值技术或理论吗？

from skimage.measure import compare_ssim
import cv2
...

image_a = cv2.imread(first)
image_b = cv2.imread(second)

gray_a = cv2.cvtColor(image_a, cv2.COLOR_BGR2GRAY)
gray_b = cv2.cvtColor(image_b, cv2.COLOR_BGR2GRAY)

_, diff = compare_ssim(gray_a, gray_b, full=True, gaussian_weights=True)
diff = (diff * 255).astype("uint8")

thresh = cv2.threshold(diff, 0, 255,
                       cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]

contours = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
contours = contours[0] if len(contours) == 2 else contours[1]

contour_sizes = [(cv2.contourArea(contour), contour) for contour in contours]


if len(contour_sizes) > 0:
    largest_contour = max(contour_sizes, key=lambda x: x[0])[1]
    x, y, w, h = cv2.boundingRect(largest_contour)
    cv2.rectangle(image_a, (x, y), (x + w, y + h), (36, 255, 12), 2)
    cv2.rectangle(image_b, (x, y), (x + w, y + h), (36, 255, 12), 2)

cv2.imwrite('image_a.jpg', image_a)
cv2.imwrite('image_b.jpg',image_b)
cv2.imwrite('thresh.jpg', thresh)

检测到最大轮廓的图像_a 检测到最大轮廓的 image_b 打谷

Answer 1

通过对给定图像之间的差异的均值进行阈值处理可以获得更好的结果。

def get_mask(img1, img2, thresh):
    if img1.shape != img2.shape:
        return
    diff = cv2.absdiff(img1, img2)
    diff = np.mean(diff, axis=2)
    diff[diff <= thresh] = 0
    diff[diff > thresh] = 255
    mask = np.dstack([diff] * 3)
    return mask

伪影可能会出现在生成的蒙版中，可以通过应用 Morphological Transformations 来减少.