我有盒子的照片。我正在尝试检测角点并从圆上标记这些角点。我为此使用以下代码:
import cv2
import numpy as np
img_file = 'Image.jpg'
img = cv2.imread(img_file, cv2.IMREAD_COLOR)
imgDim = img.shape
dimA = imgDim[0]
dimB = imgDim[1]
# RGB to Gray scale conversion
img_gray = cv2.cvtColor(img,cv2.COLOR_RGB2GRAY)
# Noise removal with iterative bilateral filter(removes noise while preserving edges)
noise_removal = cv2.bilateralFilter(img_gray,9,75,75)
# Thresholding the image
ret,thresh_image = cv2.threshold(noise_removal,220,255,cv2.THRESH_OTSU)
th = cv2.adaptiveThreshold(noise_removal, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 11, 2)
# Applying Canny Edge detection
canny_image = cv2.Canny(th,250,255)
canny_image = cv2.convertScaleAbs(canny_image)
# dilation to strengthen the edges
kernel = np.ones((3,3), np.uint8)
# Creating the kernel for dilation
dilated_image = cv2.dilate(canny_image,kernel,iterations=1)
np.set_printoptions(threshold=np.nan)
_, contours, h = cv2.findContours(dilated_image, 1, 2)
contours= sorted(contours, key = cv2.contourArea, reverse = True)[:1]
corners = cv2.goodFeaturesToTrack(thresh_image,6,0.06,25)
corners = np.float32(corners)
for item in corners:
x,y = item[0]
cv2.circle(img,(x,y),10,255,-1)
cv2.namedWindow("Corners", cv2.WINDOW_NORMAL)
cv2.imshow("Corners",img)
cv2.waitKey()
这段代码将返回我的图像,并带有带圆角的指向边,但是您可以看到错误地检测到两个边缘(盒子背面的边缘)。我知道确定角点存在一些问题,因为这里我们只是在绘制角点。谁能指导我我做错了什么地方?谢谢最佳答案
我不会说我已经达到了最好的解决方案,但是经过大量的编码,我可以获得以下内容:
为此,我遵循以下步骤:
1.首先:获取盒子的边缘
这是上面的结果:
现在,当我完成角点检测时,我一点都不满意:
那我该怎么办?
2.查找所需的角
结果,我能够获得以下信息:
我知道这并不完美,但可以随时对其进行微调。
这是拐角检测的代码:
dst = cv2.cornerHarris(dilate,2,3,0.04)
#----result is dilated for marking the corners, not important-------------
dst = cv2.dilate(dst,None)
#----Threshold for an optimal value, it may vary depending on the image---
img[dst>0.01*dst.max()]=[0,0,255]
关于python - 图像处理Opencv Python中的角点检测,我们在Stack Overflow上找到一个类似的问题:https://stackoverflow.com/questions/41681695/