Hough Lines检测到太多行

Question

我正在尝试使用opencv中的霍夫线从织物图像中提取垂直线。我应用了对比度增强功能来增强线条和双边过滤效果，以尝试去除其他织物纹理。但是，在应用轮廓线时，代码会检测整个图像上的线条。我尝试使用hough参数，但结果相同。

Input image after applying histogram equalization and bilateral filter

这里是应用了轮廓线之后的图像，红色表示检测到的线条。Output showing hough detections

我可以尝试使用哪种其他方法，以使霍夫也不会开始将细微的织物图案检测为线条？

这是我的代码：

`

    img1= cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    img2 = cv2.equalizeHist(img1)
    img3 = cv2.equalizeHist(img2)
    img4 = cv2.equalizeHist(img3)
    img5 = cv2.bilateralFilter(img4, 9, 75,75)
    cv2.imshow("threshold",img5)
    edges = cv2.Canny(img4,50,127,apertureSize = 3)
    lines= cv2.HoughLines(edges, 1, math.pi/180.0, 200, np.array([]), 0, 0)
    a,b,c = lines.shape
    for i in range(a):
        rho = lines[i][0][0]
        theta = lines[i][0][1]
        a = math.cos(theta)
        b = math.sin(theta)
        x0, y0 = a*rho, b*rho
        pt1 = ( int(x0+1000*(-b)), int(y0+1000*(a)) )
        pt2 = ( int(x0-1000*(-b)), int(y0-1000*(a)) )
        cv2.line(img, pt1, pt2, (0, 0, 255), 2, cv2.LINE_AA)

cv2.imshow('image1',img)
cv2.waitKey(0)
cv2.destroyAllWindows()`

Answer 1

您需要先对均衡后的图像进行阈值处理，然后进行形态学清理，然后再进行Canny边缘检测和轮廓线提取。使用Python / OpenCV进行以下处理。

输入：

import cv2
import numpy as np
import math

# read image
img = cv2.imread('fabric_equalized.png')

# convert to grayscale
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

# threshold
thresh = cv2.threshold(gray,165,255,cv2.THRESH_BINARY)[1]

# apply close to connect the white areas
kernel = np.ones((15,1), np.uint8)
morph = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel)
kernel = np.ones((17,3), np.uint8)
morph = cv2.morphologyEx(morph, cv2.MORPH_CLOSE, kernel)

# apply canny edge detection
edges = cv2.Canny(img, 175, 200)

# get hough lines
result = img.copy()
lines= cv2.HoughLines(edges, 1, math.pi/180.0, 165, np.array([]), 0, 0)
a,b,c = lines.shape
for i in range(a):
    rho = lines[i][0][0]
    theta = lines[i][0][1]
    a = math.cos(theta)
    b = math.sin(theta)
    x0, y0 = a*rho, b*rho
    pt1 = ( int(x0+1000*(-b)), int(y0+1000*(a)) )
    pt2 = ( int(x0-1000*(-b)), int(y0-1000*(a)) )
    cv2.line(result, pt1, pt2, (0, 0, 255), 2, cv2.LINE_AA)


# save resulting images
cv2.imwrite('fabric_equalized_thresh.jpg',thresh)
cv2.imwrite('fabric_equalized_morph.jpg',morph)
cv2.imwrite('fabric_equalized_edges.jpg',edges)
cv2.imwrite('fabric_equalized_lines.jpg',result)

# show thresh and result    
cv2.imshow("thresh", thresh)
cv2.imshow("morph", morph)
cv2.imshow("edges", edges)
cv2.imshow("result", result)
cv2.waitKey(0)
cv2.destroyAllWindows()

阈值图像：

形态清洗图像：

边缘图像：

结果霍夫线：