0

我正在尝试使用Houghlines方法在白色矩形的每一侧绘制 4 条线。
这是我正在处理的图像源图像 （2592 x 1246 图像）。

import cv2 as cv
import numpy as np
img = cv.imread("picture_compress.bmp")
img_gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
edges = cv.Canny(img_gray, 100, 200, 5)
lines = cv.HoughLines(edges, rho=2, theta=np.pi / 180, threshold=200)  # lines will be in polar coordinate system
colors = [(0, 0, 255), (0, 255, 0), (255, 0, 0), (255, 0, 255), (255, 255, 0), (0, 255, 255)]

for i, line in enumerate(lines):
    rho, theta = line[0]    # rho --> distance from the coordinate origin (0,0) (Top-Left corner of the image)
                            # theta --> line rotation angle in radius
    # getting the cos(theta) and sin(theta) value
    a = np.cos(theta)
    b = np.sin(theta)
    # getting the origin value(top-left corner of the image)
    x0 = a * rho
    y0 = b * rho
    # 2 points
    pt1 = (int(x0 + 2592 * (-b)), int(y0 + 2592 * a))
    pt2 = (int(x0 - 2592 * (-b)), int(y0 - 2592 * a))
    # draw lines on the input image
    cv.line(img, pt1, pt2, colors[i % len(colors)], thickness=3, lineType=cv.LINE_AA)
print("Total number of lines:", str(len(lines)))
cv.namedWindow("Hough", cv.WINDOW_NORMAL)
cv.imshow("Hough", img)
cv.waitKey(0)

结果我得到了Result。

从最后一张图片中，您可以看到在白色斑点的边缘绘制了多条线。

任务：

  1. 在矩形的每一侧仅绘制 4 条线的最佳方法是什么？
  2. 如何仅使用HoughLines而不是HoughLinesP来获得 4 条有限线？

--------------------------------------------------已编辑（2021 年 3 月 17 日） ------------------------------------------ --------

让我发布我正在处理的原始图像。

Fase 1：Eroded_Dilated_Image - 应用腐蚀和膨胀并填充斑点后的结果。代码：

# This function is used for cleaning the image
def erode_dilate(img, num_iter):                    
    kernel = np.ones((3, 3), np.uint8)
    erosion = cv.erode(src=img, kernel=kernel, iterations=num_iter)
    dilation = cv.dilate(src=erosion, kernel=kernel, iterations=num_iter) 
    return dilation

# This function will search for the blob with max area and will fill it
def find_draw_big_blob(img): 
    contours, _ = cv.findContours(image=img, mode=cv.RETR_TREE, method=cv.CHAIN_APPROX_SIMPLE)
    contour_area = [cv.contourArea(cnt) for cnt in contours]      # List of contours' area
    id_max_area = np.argmax(contour_area)     
    label_max_image = np.zeros(img.shape)
    draw_max_contour = cv.drawContours(image=label_max_image, contours=contours, contourIdx=id_max_area, color=255, thickness=-1)  

img = cv.imread("25559.bmp")
gray_image = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
ret1, thresh = cv.threshold(gray_image, thresh=127, maxval=255, type=cv.THRESH_OTSU)
image_erode_dilate = erode_dilate(img=thresh, num_iter=2)
big_blob = find_draw_big_blob(img=image_erode_dilate)
cv.imshow("Image", big_blob)

Fase 2: houghlines_Image - 应用hough trasform后的最终结果。我用于这个霍夫变换的代码已经在问题中了。

但最终的结果并不是我想要的结果。
我想实现这个sample_image中显示的以下结果

4

2 回答 2

1
  • 在矩形的每一侧仅绘制 4 条线的最佳方法是什么？

在矩形的每一侧仅绘制 4 条线的最佳方法是使用快速线检测器

下面你可以看到 fast-line-detector 的工作原理：

在此处输入图像描述

代码：

# Load the library
import cv2

# Load the image
img = cv2.imread("BWzd2.png")

# Convert to gray-scale
gry = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# Init. the fast-line-detector (fld)
fld = cv2.ximgproc.createFastLineDetector().detect(gry)

# Detect the lines
for line in fld:

    # Get current coordinates
    x1 = int(line[0][0])
    y1 = int(line[0][1])
    x2 = int(line[0][2])
    y2 = int(line[0][3])

    # Draw the line
    cv2.line(img, (x1, y1), (x2, y2), (255, 0, 255), 5)

# Display
cv2.imshow("img", img)
cv2.waitKey(0)

结果：

在此处输入图像描述

于 2021-03-03T11:49:23.827 回答
1

在您的 Python/OpenCV 代码中，只需将阈值增加到 250 或将 theta 角加倍。

输入：

在此处输入图像描述

1) 增加门槛

lines = cv.HoughLines(edges, rho=2, theta=np.pi / 180, threshold=250)  # lines will be in polar coordinate system


import cv2 as cv
import numpy as np
img = cv.imread("picture_compress.png")
img_gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
edges = cv.Canny(img_gray, 100, 200, 5)
lines = cv.HoughLines(edges, rho=2, theta=np.pi / 180, threshold=250)  # lines will be in polar coordinate system
colors = [(0, 0, 255), (0, 255, 0), (255, 0, 0), (255, 0, 255), (255, 255, 0), (0, 255, 255)]

result = img.copy()
for i, line in enumerate(lines):
    rho, theta = line[0]    # rho --> distance from the coordinate origin (0,0) (Top-Left corner of the image)
                            # theta --> line rotation angle in radius
    # getting the cos(theta) and sin(theta) value
    a = np.cos(theta)
    b = np.sin(theta)
    # getting the origin value(top-left corner of the image)
    x0 = a * rho
    y0 = b * rho
    # 2 points
    pt1 = (int(x0 + 2592 * (-b)), int(y0 + 2592 * a))
    pt2 = (int(x0 - 2592 * (-b)), int(y0 - 2592 * a))
    # draw lines on copy of the input image
    cv.line(result, pt1, pt2, colors[i % len(colors)], thickness=3, lineType=cv.LINE_AA)
print("Total number of lines:", str(len(lines)))
cv.namedWindow("Hough", cv.WINDOW_NORMAL)
cv.imshow("Hough", result)
cv.waitKey(0)

cv.imwrite("picture_compress_lines1.png", result)

在此处输入图像描述

2）增加你的theta，例如加倍：

lines = cv.HoughLines(edges, rho=2, theta=2*np.pi / 180, threshold=200)  # lines will be in polar coordinate system


import cv2 as cv
import numpy as np
img = cv.imread("picture_compress.png")
img_gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
edges = cv.Canny(img_gray, 100, 200, 5)
lines = cv.HoughLines(edges, rho=2, theta=2*np.pi / 180, threshold=200)  # lines will be in polar coordinate system
colors = [(0, 0, 255), (0, 255, 0), (255, 0, 0), (255, 0, 255), (255, 255, 0), (0, 255, 255)]

result = img.copy()
for i, line in enumerate(lines):
    rho, theta = line[0]    # rho --> distance from the coordinate origin (0,0) (Top-Left corner of the image)
                            # theta --> line rotation angle in radius
    # getting the cos(theta) and sin(theta) value
    a = np.cos(theta)
    b = np.sin(theta)
    # getting the origin value(top-left corner of the image)
    x0 = a * rho
    y0 = b * rho
    # 2 points
    pt1 = (int(x0 + 2592 * (-b)), int(y0 + 2592 * a))
    pt2 = (int(x0 - 2592 * (-b)), int(y0 - 2592 * a))
    # draw lines on copy of the input image
    cv.line(result, pt1, pt2, colors[i % len(colors)], thickness=3, lineType=cv.LINE_AA)
print("Total number of lines:", str(len(lines)))
cv.namedWindow("Hough", cv.WINDOW_NORMAL)
cv.imshow("Hough", result)
cv.waitKey(0)

cv.imwrite("picture_compress_lines2.png", result)

在此处输入图像描述

霍夫线的文本数据说：

Total number of lines: 5

但我只看到 4 行。

于 2021-03-03T16:48:43.150 回答