python - 检测和定位两个与文本有区别的图像中的区域（普通/曲线/旋转）

Question

我有两张相同的图片，唯一的区别是其中一张包含一些文字。我想围绕该文本制作一个边界框或多边形框。为此，我尝试比较这两个图像并测量差异区域，然后在不同区域或简单的文本区域周围制作一个边界框。

原始图像

文字+原图

before = cv2.imread('before.jpg')
after = cv2.imread('after.jpg')

# Convert images to grayscale
before_gray = cv2.cvtColor(before, cv2.COLOR_BGR2GRAY)
after_gray = cv2.cvtColor(after, cv2.COLOR_BGR2GRAY)

# Compute SSIM between two images
(score, diff) = compare_ssim(before_gray, after_gray, full=True)
print("Image similarity", score)

# The diff image contains the actual image differences between the two images
# and is represented as a floating point data type in the range [0,1] 
# so we must convert the array to 8-bit unsigned integers in the range
# [0,255] before we can use it with OpenCV
diff = (diff * 255).astype("uint8")

# Threshold the difference image, followed by finding contours to
# obtain the regions of the two input images that differ
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]

or c in contours:
    area = cv2.contourArea(c)
    if area > 40:
        x,y,w,h = cv2.boundingRect(c)
        cv2.rectangle(before, (x, y), (x + w, y + h), (36,255,12), 2)
        cv2.rectangle(after, (x, y), (x + w, y + h), (36,255,12), 2)

问题是，它无法使用旋转文本和曲线形状文本的边界框进行捕获。请看下图：

比较结果

通缉

我想在文本周围实现适当的边界框或多边形框，无论它是旋转的还是曲线的。预期的演示输出如下所示：

预期结果

标签： pythonopencvimage-processing

Answer 1

您需要计算每个文本位置的点序列。

for c in contours:
    area = cv2.contourArea(c)
    if area > 40:
        x, y, w, h = cv2.boundingRect(c)
        rectangle = cv2.minAreaRect(c)
        box = np.int0(cv2.boxPoints(rectangle))
        cv2.drawContours(after, [box], 0, (0, 191, 255), 2)

输出：