【发布时间】:2016-08-21 05:42:30
【问题描述】:
我需要检测给定图像中的最长线,我的图像将与此类似:
我在细化后尝试过,但是细化后图像变得像素化并且没有保持直线。
还有其他方法可以解决这个问题吗?
谢谢 光辉
【问题讨论】:
标签: python opencv image-processing contour edge-detection
我需要检测给定图像中的最长线,我的图像将与此类似:
我在细化后尝试过,但是细化后图像变得像素化并且没有保持直线。
还有其他方法可以解决这个问题吗?
谢谢 光辉
【问题讨论】:
标签: python opencv image-processing contour edge-detection
你觉得这个解决方案怎么样?
我在代码中包含了解释。总体思路是先做一个阈值化,提取黑色区域,然后寻找轮廓,挑出最长的。
Dilation 已经完成了挑选出指针的所有工作,但我在里面留下了一些替代代码,用于查找最长的轮廓,以备不时之需。
#!/usr/bin/env python
import sys
import numpy as np
import cv2
from matplotlib import pyplot as plt
img = cv2.imread('image.jpg',0)
print img.shape
h, w = img.shape[:2]
# Drop top and bottom area of image with black parts.
img= img[100:h-100, :]
h, w = img.shape[:2]
# Threshold image
ret,th1 = cv2.threshold(img,50,255,cv2.THRESH_BINARY)
# get rid of thinner lines
kernel = np.ones((5,5),np.uint8)
th1 = cv2.dilate(th1,kernel,iterations = 3)
# Determine contour of all blobs found
_, contours0, hierarchy = cv2.findContours( th1.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
contours = [cv2.approxPolyDP(cnt, 3, True) for cnt in contours0]
# Draw all contours
vis = np.zeros((h, w, 3), np.uint8)
cv2.drawContours( vis, contours, -1, (128,255,255), 3, cv2.LINE_AA)
# Draw the contour with maximum perimeter (omitting the first contour which is outer boundary of image
# Not necessary in this case
vis2 = np.zeros((h, w, 3), np.uint8)
perimeter=[]
for cnt in contours[1:]:
perimeter.append(cv2.arcLength(cnt,True))
print perimeter
print max(perimeter)
maxindex= perimeter.index(max(perimeter))
print maxindex
cv2.drawContours( vis2, contours, maxindex +1, (255,0,0), -1)
# Show all images
titles = ['Original Image','Threshold','Contours', 'Result']
images=[img, th1, vis, vis2]
for i in xrange(4):
plt.subplot(2,2,i+1)
plt.imshow(images[i],'gray')
plt.title(titles[i]), plt.xticks([]), plt.yticks([])
plt.show()
[编辑]
您可以添加更多代码来将轮廓的主轴确定为一条线,如下所示:
# Determine and draw main axis
length = 300
(x,y),(MA,ma),angle = cv2.fitEllipse(cnt)
print np.pi , angle
print angle * np.pi / 180.0
print np.cos(angle * np.pi / 180.0)
x2 = int(round(x + length * np.cos((angle-90) * np.pi / 180.0)))
y2 = int(round(y + length * np.sin((angle-90) * np.pi / 180.0)))
cv2.line(vis2, (int(x), int(y)), (x2,y2), (0,255,0),5)
print x,y,x2,y2
【讨论】: