使用 python opencv 检测刻度线

Question

所以我得到了一个盒子的图像，盒子里有许多大小不一的刻度线，就像一把尺子。如下图：

This is the input picture

到目前为止，我的情况是，通过边缘检测，我只能将外部矩形检测为矩形，但不能检测矩形内的任何刻度线。代码如下：

import numpy as np
import cv2


image = cv2.imread('images\Ruler.png')
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blur = cv2.GaussianBlur(gray, (3, 3), 0)
edges = cv2.Canny(blur, 50, 200)
cnts, hierarchy = cv2.findContours(edges, cv2.RETR_LIST, 
cv2.CHAIN_APPROX_SIMPLE)

corner_points = []


for index, cnt_points in enumerate(cnts):
    perimeter = cv2.arcLength(cnts[index], True)
    approx = cv2.approxPolyDP(cnts[index], 0.02 * perimeter, True)
    corner_points.append(approx)


    x, y, w, h = cv2.boundingRect(corner_points[index])
    cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 2)

print(corner_points)
cv2.imshow("Contour", image)
cv2.waitKey(0)
cv2.destroyAllWindows()

我希望生成的图像类似于下图所示：

Ideal result

正如您所见，不仅检测到刻度线（红色轮廓）和外部矩形（绿色轮廓），而且您还能够将刻度线与外部矩形区分开来。我也在尝试获取刻度线角点的像素位置，以及在我的代码中看到的我将角点存储到“角点 = []”

我也不确定刻度线是否被视为粗线或矩形。因此位置角点可以是刻度线“线”的两个端点，也可以是刻度线“矩形”的 4 个顶点。

Answer 1

import cv2

img = cv2.imread('images/Ruler.png', cv2.IMREAD_GRAYSCALE)
h, w, _ = img.shape

bw = img > 128
corner_points = []
# if the pixel length of a line is higher than this threshold
# add the start and end points to corner_points
accepted_length = 10

for i in range (0, h):
    start = -1  # the first True pixel in the row
    stop = -1  # the first False pixel after start
    for j in range (0, w):
        if bw(i,j) and start is -1:
            start = j
        if start is not -1 and not bw(i,j):
            stop = j
            # I added 50 here to avoid adding floor and ceil lines
            if stop - start > accepted_length and stop - start < 50:
                corner_points.append([start end])
            continue