图像处理中的角点检测Opencv Python [英] Corner detection in Image processing Opencv Python

问题描述

我有一个盒子的图像。我试图检测角落并从圆圈标记这些角落。我使用以下代码：

I have an image of the box. I am trying to detect corners and mark those corner from circles. I am using the following code for this:

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()

此代码将返回带有圆圈的指向边缘的图像但您可以看到两条边（背面的边缘） （盒子）检测不正确。我知道在确定角落时存在一些问题，因为我们只是在绘制角落。任何人都可以指导我在哪里做错了吗？感谢

This code will return my image with pointing edges with circles but you can see that two edges (edges at the back of the box) are detected incorrectly. I know there is some problem in determining the corners because here we are just plotting the corners. Can anyone guide me where I am doing it wrong ? Thanks

推荐答案

我不会说我已经达到了最佳解决方案，但经过相当多的编码后我得到了以下内容：

I wouldn't say I have reached the best solution, but after quite a lot of coding I was able to obtain the following:

为了获得这一点，我按照以下步骤操作：

To obtain this I followed the following steps:

1。第一：获取方框的边缘

1. First: Obtain the edges of the box

• 我执行了双边过滤灰度图像。


• 使用 Canny边缘检测找到边缘。


• 使用形态膨胀增强边缘。

• I performed bilateral filtering on the grayscale image.
• Found the edges using Canny edge detection.
• Enhanced the edges using morphological dilation.

这是以上结果：

现在当我做了角落检测，我一点也不满意：

Now when I did Corner detection, I was not at all satisfied:

那我该怎么办？

2。寻找所需的角落

2. Finding desired corners

• 我模糊使用大小窗口扩大图像9x9。


• 然后将 Harris角点检测应用于此模糊图像。

• I blurred the dilated image using a window of size 9x9.
• Then applied Harris corner detection to this blurred image.

结果我得到了这个：

我知道它并不完美，但可以随时进行微调。

I know it is not perfect but it can always be fine tuned.

以下是角点检测的代码：

Here is the code for corner detection:

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]

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